Digital fingerprinting - Essay Example

Digital fingerprinting   Contents page Thesis approval page Acknowledgments Table of contents List of tables List of illustrations (charts, graphs, figures) Text (chapters of the manuscript) Endnotes Appendices References TITLE The Use of Digital Fingerprinting in Crime Control – Analyzing two techniques A RESEARCH PROJECT SUBMITTED TO XXXX UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF FORENSIC SCIENCES MAY 2009 By Hector Sanchez Masters Thesis Committee: , Chairperson , Supervisor , Supervisor MASTERS THESIS APPROVAL FORMS We certify that we have read the project of ………….. entitled Instructions for the Preparation of the Masters Thesis and that, in our opinion; it is satisfactory in scope and quality as a thesis for the degree of Master of Forensic Sciences at National University. Approved by: , Chairperson Date: , Supervisor Date: , Supervisor Date: Lead Faculty of Forensic Sciences Program Date: Acknowledgments Abstract This research deals with the improvements in the technological aspects of digital fingerprinting and focuses on its application and contexts as also its uses and processes. The structures and imaging techniques and the functions and processing and transmission of images are discussed, along with a comparative analysis of two relevant techniques. The two techniques show differences in fingerprinting methods as the first patent deals with identification of fingerprints and its applications and the second technique deals with transmission and storage of fingerprints through a mobile device. Advanced methods in digital fingerprinting could highly enhance the process of access, scanning, storage, analysis and matching of fingerprints through enhanced ridges and patterns study and also through advanced transmission techniques as seen in the comparative analysis of both the techniques that seem to differ in functionalities. Keywords: Digital fingerprinting, scanning, crime control, investigation, evidence, matching, fingerprints, digital technology, forensic science. Table of Contents Acknowledgements iv Abstract v List of Tables vii Table of Illustrations viii Chapter I: Introduction Background of the Study Problem Statement Purpose and Objectives of the Study Rationale of the Study Definition of Terms Limitations of the Study Research Hypotheses Summary of Remaining Chapters Chapter II: Literature Review The Process of Fingerprinting Defining Digital Fingerprinting Link between Crime Control and Digital Fingerprinting Chapter III: Methodology Setting Description of the Patents Description of the Instrument Procedures Chapter IV: Results Factors identified Comparative Analysis of Case Study Chapter V: Discussion, Conclusions and Recommendations Discussion Problems/Limitations Conclusions Recommendations for Future Research References List of Tables Table 1.1. Table for Hypothesis Testing………………………………...................... Table 3.1: Results Table for Patent I............................................................................ Table 4.1: Results table for Patent II............................................................................ Table 4.2: Results Table for Comparative Analysis………………............................. Table of Illustrations Figure 4.1: Fingerprint Illustration………................................................................... Figure 4.2: Digital Fingerprinting – Factors and Applications………………............ Figure 4.3: Patent I for Digital Fingerprinting……………………..…………........... Figure 4.4: Patent II for Digital Fingerprinting………………………........................ Figure 4.5: Comparing methods of fingerprinting…................................................... Text Chapter I: Introduction Background of the Study: This study is based on research questions that will aim to examine the use of digital fingerprinting and such other techniques in crime control and crime investigation and how the methods of storage of digital fingerprints in databases could have an impact on the information accessibility in general. The study will draw on several questions and research objectives and analyze other similar research studies that have dealt with an explanation of digital fingerprinting, its storage and classification systems and its general use in gathering evidential information in forensic science (Kirby, 1990). The study will use data from patents on equipment and methods used for digital fingerprinting and analysis and two such patents for fingerprinting techniques are analysed here. Problem Statement: The problem that is studied here includes the uses and applications of digital fingerprinting and the differences in equipment, classification and storage of fingerprints. It is also examined how these issues affect accessibility to information and especially crime related investigation. Purpose and objectives of the Study: The objectives of this research project would be to investigate and link the relations between digital fingerprinting techniques, data storage and classification and the accessibility to evidential information using equipment or patented technology (Kirby 1990, Lofyenberg 2001). The objective is to study the relation between technology and crime and criminal evidence, the use and application of digital fingerprinting, how these are accessed, stored and classified, what classification techniques are appropriate and how the entire process benefits the forensic sciences, especially in matters of criminal evidence and investigation. Rationale of the Study: The rationale of the study is related to the analysis of crime and forensic technology and the study is important because it shows how classification and patented technology in digital fingerprinting can improve or change the accessibility of information required for forensic studies and investigations. Limitations of the Study: The limitations of the study are the time and resources within which it has been undertaken. The time limit being short, only secondary research analysis could be performed and primary data as used in the study has been obtained from papers showing patent technology on digital fingerprinting. The limitations of resources also meant that very few resources are available and few studies have been undertaken on digital fingerprinting and no theoretical framework has been very well established and all approaches remain controversial. Theoretical Framework: The theoretical framework and methodology are based on comparative qualitative analysis of the data obtained and in this case two case studies of patents in fingerprinting technology are used. Research Hypotheses: The research hypothesis is based on the proposition that digital fingerprinting techniques and newer and advanced methods of classification, storage and advanced technology could highly enhance the evidential information obtained and this would be particularly beneficial to forensic sciences. The four testable hypotheses developed and tested for this thesis would be the basis of the entire research project that will focus on the different patented technologies for digital fingerprinting and whether these could be compared on the basis of their use in crime control. Table 1. Hypothesis Table The hypotheses are given as follows: Hypothesis 1.Digital Fingerprinting Techniques are comparable and can be used in patented technologies. Hypothesis 2. Digital fingerprinting methods are suitable for monitoring purposes. Hypothesis 3.Digital fingerprinting techniques tend to have similar classification, access and storage methods. Hypothesis 4.Digital fingerprinting techniques are not the primary tool in forensic investigation. Chapter II: Literature Review Digital fingerprinting and all digital architecture are closely related to crime control and crime law, a part of the overall cyber laws. Cyber law tends to regulate cyberspace although the architecture itself could help in constraining all forms of crime. Research on crime control relate to real space and can also apply to cyberspace and the cynernetic realm. The regulation of cyberspace depends on architectural, legal, economic and social constraints. Katyal (2003) shows how real space architecture tends to inform the regulation of computer crime in cyberspace. Computer crime causes major damage to the US economy as even a single virus can wreak havoc to computer systems and cost billions of dollars and 90% corporate houses have detected security breaches to their computer and information systems even as their information has been hacked. Yet there seems to be a gap between architecture in real space and that of cyberspace and there is very little analysis of digital architecture and relationship to crime and all real space architectural literature on crime prevention has not been effective enough to garner readership among the computer engineers and this means that the difference between real and cyberspace has not been overtly studied although the architecture that has been used to solve crimes in the real space could also be used digitally. Offline problems could as well be solved online as the difference between real and cyberspace could be resolved especially with new digital features of wireless networking, cameras, internet and so on. As digital architecture delineates similarities and differences between cyberspace and real space, digital evidence seems to be associated with understanding computer crime and the role of forensic science and computers in cyber crime. Casey (2000)suggested that digital evidence or evidence stored and transmitted by computers could be used to solve cases related to a large number of crimes including homicide, rape, abduction, child abuse, child pornography, drug trafficking, computer intrusion and hacking, fraud, scams, harassment, stalking and terrorism. A large number of criminals use computers and networks although very few have substantial knowledge about the technical, evidential or legal issues involved in crime and digital evidence. Casey aimed to provide a study on the link between computer crime and digital evidence and this involved areas of forensic science, law enforcement, computer security as well. The paper deals with the relations between computers and crime and how these can be used as evidence and can provide further insights into profiling and investigations as also criminal motivation. Some of the major topics as studied in the paper includes “Components of computer networks, Use of computer networks in an investigation , Abuse of computer networks, Privacy and security issues on computer networks, The law as it applies to computer networks”(Casey 2000) Fingerprinting techniques have however reached advanced levels and Isenor and Zaky discussed an algorithm for encoding and matching of fingerprints although the algorithm may not be sensitive to the imperfections related to noise, distortion and displacement (Isenor and Zaky, ).The paper discussed fingerprint coding using graphic matching techniques as fingerprints are represented in the form of graphs and the nodes of the fingers are seen as ridges hen printed. The edges of the graph could connect the intersecting ridges showing topological relationships in the fingerprint. The algorithm could be implemented in proper fingerprint images and the study was conducted after the implementation of an algorithm deciphering features and details of the fingerprint. Jain and Prabhakar (1999) discussed fingerprint classification as an important mechanism in building a database of fingerprints as classification largely makes storage and identification of data less time consuming and more accurate. Any database should have some classification framework and any accurate and consistent classification systems of fingerprint classification could be especially useful in techniques of matching if criminal evidence is to be sorted from a large database. Fingerprint classification should be based on accuracy where details of the fingerprints such whorls, loops and arches should be considered in detail. Classification helps in analyzing the category to which a finger print belongs and so with that knowledge matching fingerprints from the same category could be used as evidence. According to Ratha et al (1996) the use of multimedia technology, suggests a need for efficient techniques to search large image databases. Large databases tend to store images that could be match with evidence from crime related and all other investigation. Because of the unique features of such databases they cannot be treated as digital libraries as contextual formats are presented in images and the two dimensional image data may be complex and the entire complexity of context, storage and presentation makes representation of images even more difficult. The way in which data is represented and especially the invariant representation of data could have many associated issues when considering the techniques of storage of images in a database. It may be difficult to understand how a content based retrieval technique would work although the approaches of categorization and retrieval based on shape, texture and color of images may not be too successful. However representation on the basis of these properties could be applicable even in noise and distortions although there might be several constraints to this as they deal with retrieval performance and examination of query images. A graphical representation of the fingerprint in digital form is given below: Fig 1 –fingerprint shows the ridges and singular points, patterns that make it unique Fingerprint databases sometimes store distorted images and this is common due to the elasticity of skin which may expand or contract affecting the imaging. However ridges and other features such as pattern class could also be considered while differentiating images and feature based matching could thus be most appropriate for indexing of database. There could also be a multilevel indexing and implementation of search engines to determine fingerprint databases in the public domain. Qinshi et al (2001) discussed a new approach to fingerprint classification based on singularities and pseudoridge analysis and highlights the fact that noise and distortions that are common in fingerprint images and may prevent the noting of the number and position of singularities and delta points, features that are used in structural classification methods. The poor quality of fingerprint images may lead to incorrect singular points and classification which would have to deal with more accurate information on singularities will not work in this case. Thus psuedoridge analysis could be appropriate in this case and pseudoridge tracing and analysis could be used instead of extraction of the exact positions of singularities and Qinshi et al have explained that for 4000 images, classification accuracy could be 95%. Fingerprint reference-point detection has been studied by Liu et al (2005) who discussed fingerprint recognition algorithm as important in rotation and translation of fingerprint image. The study is based on an understanding of reference points and orientation as a unique reference point could be used for rotational alignment. The paper highlights the use of an algorithm that could be used to determine and develop reference points and corresponding reference orientation for the fingerprints. A reliable orientation method is also used in this case and a smoothing method helps in removing noise as distortions, and performs multi scale analysis for consistency of data and information during the imaging process. The orientation differences in case of different images is analysed and the local ridge orientations are also considered to understand reference points and intervals and this in turn helps the computation of reference orientation with high accuracy for fingerprints. In another presentation of fingerprint classification using multi-channel approach of pattern analysis and machine intelligence, Jain and Prabhakar uses a novel representation as the finger code and makes a classification of fingerprints based on a two stage classifier. This new classification system has been tested on 4000 images (Jain and Prabhakar, 1999) and a classification accuracy of 90% has been attained in each case. There are five class and four class stages of classification and usually four class stages provide more accuracy although according to the authors classification with five class verification could reach above 96% although image rejection could be high and 32% images will have to be rejected if very high levels of accuracy is to be reached with the four and five point classification. Initially a search was done using search terms such as fingerprint, digital fingerprinting, fingerprinting crime, storage of images, data etc. The search was done with the help of internet search engines such as google scholar. The search returned several relevant articles and books results that dealt with digital fingerprinting and crime control. Digital fingerprinting is largely used for crime control and the stored images and data could be used to match with evidential information and images related to findings. Digital fingerprinting methods store fingerprints images that show ridges and singularities and peculiar features and fingerprints are distinguished and categorized in accordance with their shapes, texture, ridges, color, patterns (Kirby, 1990). It has been suggested in several research studies that ridges and patterns are the most effective data that could be used for the analysis and categorization of fingerprints and finally matching techniques are applied to suggest whether the evidential information obtained in a particular context could be well related to the images stored in the database of collected fingerprints. The next part, methodology is however focused on patented technologies and equipment that could make such categorization possible and the equipment discussed here would be in accordance with whether they enhance the process and technique of digital fingerprinting. The two patented techniques discussed at length here deal with claims related to what the equipment can achieve and what unique features would help the technology to improve the digital fingerprinting process especially as it relates to crime (Casey, 2000). The method is a qualitative analysis which means after a google search of patents with search terms of digital fingerprinting and crime, the results returned several patents available and two of the patents were examined in some detail. These patents were then evaluated and their claims compared to understand what changes and improvements they could bring to the technique of digital fingerprint and how these could be used successfully for the control of crime (Suggs et al, 2002, Katyal 2003). The different attributes of digital imaging and the defining characteristics of fingerprints with ridges and patterns have also been highlighted. The next part was however defining the methods with which this study could be carried out. A qualitative research analysis between two patent claims have been selected as providing appropriate data for the study as there are limitations in terms of acquiring real data as related to digital fingerprinting. Chapter III: Methodology This section of the research deals with the methodology in which the appropriate methods for the study are chosen and described. The methodology is based on a comparative qualitative analysis between two patented technologies that deal with digital fingerprinting and the comparisons are based on the claims of these patents that provide unique benefits for the storage, classification and application of digital fingerprints as evidence in many cases. The methodology that is based on a comparative analysis of the two resulting data tables obtained from the patents would be focused on obtaining results although the results will have to be in accordance with the four testable hypothesis identified. To state the hypotheses once again to bring out the related methodology in the analysis for each hypothesis, these are: Testable hypothesis One – Digital Fingerprinting Techniques are comparable and similar in several respects and could thus be used in patented technologies in a way that would allow generalization of research findings Testable hypothesis Two – All digital fingerprinting methods could be suitable for monitoring purposes and would thus be effective in crime control Testable hypothesis Three – All digital fingerprinting techniques tend to have similar classification, access and storage methods so that they could have a common framework for applicability Testable hypothesis Four – Digital fingerprinting techniques as used commonly in all patented technologies is the most effective method of crime control and criminal investigation and thus the primary tool in forensic investigation Hypothesis One - The first hypothesis as to whether digital fingerprinting techniques are comparable is definitely valid and correct although they may not be similar so research findings could be generalized when two techniques are compared as results indicating digital fingerprinting methods in general, yet there may be differences. Data for testing this hypothesis are obtained from a comparative analysis of the two techniques that are described. This hypothesis requires that the two basic techniques compared here need to be analyzed on the basis of functionality. The data suggesting a comparable or similar pattern of functions of the two techniques tend to establish the hypothesis. The first hypothesis stating the basic or foundational similarity of digital fingerprinting techniques and their comparability would mean that this hypothesis is true and correct. Hypothesis Two - The second testable hypothesis that all digital fingerprinting methods and equipment would have similar applications and could be especially used for crime control and monitoring could also be effectively true as although methods of obtaining and analyzing data may differ for the different fingerprinting techniques, and the way they are used could vary, the basic purpose of monitoring and identification could be well used in all aspects of forensic science including crime control. The data obtained from the two digital fingerprinting techniques have been subject to qualitative analysis to show where they differ and how they are similar and the qualitative comparative analysis suggest that the features of the two techniques could be used for monitoring purposes so the hypothesis on applicability of the techniques remain true and valid. Hypothesis Three- The third hypothesis that all fingerprinting techniques have similar identification, classification or storage methods may not be true or valid as it is seen from these two comparative case studies that identification and transmission of information are different and when one uses identification as the basic functionality, the other technique is focused on scanning and storage of data. Thus even though there may be some functional similarities structurally these equipment would vary greatly. The third hypothesis tested that all digital fingerprinting techniques has been considered as not a valid hypothesis as there could be varying methods of identification as seen from the comparative qualitative data analysis of the two techniques. Hypothesis Four The fourth testable hypothesis is whether digital fingerprinting itself is the most common method of crime control. This could be untrue once again and although fingerprinting techniques are very sophisticated and one of the most effective techniques of identification, it is controversial whether it is the most effective tool in criminal investigation. Again this would require extensive comparisons of research studies and published papers to suggest whether there are better and more effective methods available other than fingerprinting for adequate crime control. Considering data and applications of digital fingerprinting on crime control, the fourth hypothesis claiming that digital fingerprinting is the most effective method of crime control is considered as not valid. The hypotheses above woul be tested and validated with the help of the comaprison of techniques used for the two patents described. Since the two patents could be compared qualitatively, a list of features of these patented devices are presented in a tabular format to show how the two formats could be compared. The general search as was conducted earlier and the literature and research studies available were selected for the background review. The research papers were studied in accordance with the research questions and the literature review dealt with classification and categorization of fingerprints as also the applicability of digital fingerprinting in general and for the control of crime through matching techniques. Qualitative and quantitative analysis are the two most important research methods in such a study and as quantitative data has not been available, the primary data taken here have been obtained via google search and patent claims have been considered as the data for analysis. Whereas qualitative analysis analyses and evaluates qualitative data and treats the content sometimes in a comparative manner discussing features and attributes of the objects of analysis, the quantitative analysis is about analyzing and interpretation of quantitative data and measurements that are taken to represent content with values that are used to calculate means, SDs and an explanation is provided of the quantitative measures obtained to determine whether the research objectives have been met or whether the hypothesis tested has been correct (Bryman, 2008). Qualitative measures are more appropriate for this study as the features of two patented techniques are being compared rather than data from surveys and reports (Bryman, 2008). The methodology for the study of two patents on digital fingerprinting is based on a comparative analysis of the methods of the fingerprint technologies, the storage and access of data and identification or matching of fingerprint with images already stored. This means storage and access to fingerprint data could be made available only when there is comparison of fingerprints obtained with that stored on the database. One of these is an identification system and the other patent is a mobile storage and scanning system so they seem to have different functionalities although both could be used together as one system and technique seems to complement the other. The study involves analyzing the first patent that involves study of a gray scale image that is digitized to bring out the precise and elaborate image of the fingerprints. The second patent includes a portable image collection unit and a transmission device that would help in basic identification of the image collected to match with the database of images. These two patents and reports of the patents form the primary data source for this study and as this is best analysed qualitatively using comparisons of descriptions, processes and functions rather than quantitative measures of means and correlations, the most appropriate methodology chosen for the analysis of primary data obtained is the comparative qualitative analysis. The methodology has been selected so that the research question on how advanced digital fingerprinting technology affects crime control, could be understood and answered. Chapter IV: Results (Data) Two Patents are compared in the results or data section and a comparative analysis is drawn using qualitative data. The data will be mainly presented in the form of comparative features of two devices that could be used in digital fingerprinting methods. Thus the comparison here is between features and between structural and functional similarities and differences of techniques presented. The results are presented in the form of tables and tables 1 and 2 focus on the general information related to the patented techniques, their features and functions and how they are an important part of digital fingerprinting technology providing step by step analysis of the methods and stages of acquiring fingerprints and storing and interpreting the information accessed. Patent I deals with technology related to fingerprint identification through enhanced grey scale imaging and increases precision and makes imaging more accurate and detailed (Ort et al, 1997/2001). Patent II is a technique of scanning, processing and transmitting fingerprints images through a wireless transmission process to a mobile unit which then compares data and images stored in a large database resulting in identifying data already stored and matching methods are then followed to identify the individual whose fingerprints were taken (Fishbine et al, 1995/2009). The stages and processes are explained in detail to provide a framework for the functions and the structures that could be used for enhanced capability of the forensic procedures and imaging applications. PATENT – I Fingerprint identification system - James R. Ort et al Patent number: 5926555 Filing date: Apr 3, 1997 Issue date: Jul 20, 1999 Inventors: James R. Ort, Douglas L. Lange, Frederick W. Kiefer, Raymond J. Dennison Assignee: Calspan Corporation U.S. Classification 382/124; 382/260 International Classification G06K 900 Table 1 – Patent I Apparatus used as: means for converting a fingerprint image into a digitized gray scale image comprising a plurality of individual pixels; means for determining the ridge angle and image quality of the fingerprint image at a plurality of regularly spaced individual pixels to create a Ridge Angle Map and an image quality map; and means for recording said Ridge Angle Map at those locations where the image quality is above a predetermined level, and means for recording said image quality map of said fingerprint image. means for enhancing the gray scale to provide a uniform contrast over the entire fingerprint image. means for down-sampling the contrast enhanced image to limit the number of pixels analyzed. means for determining the ridge angle and said means for determining image quality of the fingerprint image includes means for generating a gradient map of the fingerprint image, and means for defining a calculation kernel over which the ridge angle determination is made by reference to said gradient map; and means for causing the calculation kernel to traverse over said gradient map in a predetermined increment over the pixels comprising the fingerprint image. means for assigning the same ridge angle and quality values assigned to each of said plurality of pixels analyzed to surrounding pixels. means for determining the frequency of the ridges in a fingerprint at said regularly spaced intervals. method for generating a machine readable record of an image of a fingerprint, said method comprising the steps of converting a fingerprint image into a digitized gray scale image comprising a plurality of individual pixels; determining the ridge angle and image quality of the fingerprint image at regularly spaced individual pixels to create a Ridge Angle Map and an image quality map; and recording said Ridge Angle Map and said image quality map of said fingerprint image. means for enhancing the gray scale to provide a uniform contrast over the entire fingerprint image; and down-sampling the contrast enhanced image to limit the number of pixels analyzed. generating a gradient map of the fingerprint image, and defining a calculation kernal over which the ridge angle determination is made with reference to said gradient map; and traversing the calculation kernal over said gradient map in predetermined increments over the pixels comprising the fingerprint image. 11. The method of claim 8 wherein the step of determining the ridge angle and image quality of the fingerprint image at regularly spaced individual pixels to create a Ridge Angle Map and an image quality map is performed by the Direct Estimation of Static Fields process. step of smoothing the Ridge Angle Map and the image quality map. step of smoothing the Ridge Angle Map is performed by the process of erosion and dilation. step of smoothing the image quality map is performed by the process of Fourier filtering. step of determining the frequency of the ridges in a fingerprint at said regularly spaced intervals to create a Ridge Frequency Map. step of smoothing the Ridge Frequency Map. the smoothing step is performed by Fourier filtering. A method of generating a machine readable record of an image of a fingerprint comprising the steps of converting a fingerprint image into a digitized gray scale image comprising a plurality of individual pixels; enhancing the gray scale to provide a uniform contrast over the entire fingerprint image; and down-sampling the contrast enhanced image to limit the number of pixels to be analyzed; determining the ridge angle and image quality of the fingerprint image at regularly spaced individual pixels to create a Ridge Angle Map and an image quality map, including the steps of generating a gradient map of the fingerprint image, and defining a calculation kernal over which the ridge angle determination is made with reference to said gradient map; and traversing the calculation kernal over said gradient map in predetermined increments over the pixels comprising the fingerprint image; and recording said Ridge Angle Map and said image quality map of said fingerprint image. the step of smoothing the Ridge Angle Map and the image quality map. step of smoothing the Ridge Angle Map is performed by the process of erosion and dilation. the step of smoothing the image quality map is performed by the process of Fourier filtering. the step of determining the frequency of the ridges in a fingerprint at said regularly spaced intervals to create a Ridge Frequency Map. the step of determining the frequency of the ridges includes the steps of establish at each selected pixel a line perpendicular to the ridge flow, sample a predetermined number of pixels on both sides of said perpendicular line, and determine the frequency of the ridges by calculating a power spectrum from a Fourier transform. establishing a plurality of lines parallel to said perpendicular lines and placed on both sides of said perpendicular line selected pixel, sampling a predetermined number of equally spaced pixels along both said perpendicular line and said plurality of lines, and averaging the samples of each line prior to determining the frequency. the step of smoothing the Ridge Frequency Map. the smoothing step is performed by Fourier filtering. Data from Google Patents on Digital Fingerprinting PATENT - II Portable fingerprint scanning apparatus for identification verification - Glenn M. Fishbine et al Patent number: 5467403 Filing date: Mar 31, 1993 Issue date: Nov 14, 1995 Inventors: Glenn M. Fishbine, Robert J. Withoff, Theodore D. Klein Assignees: Digital Biometrics, Inc. Primary Examiner: Larry J. Prikockis U.S. Classification 382/116; 382/127; 382/313; 348/158; 34082534 International Classification G06K 922 Table 2 – Patent -II The Apparatus is claimed as A portable apparatus for identification verification, comprising: a portable image collection unit including: a fingerprint scanner comprising a finger prism having an opaque bottom surface, a finger receiving surface and two side surfaces; a light for illumination of the finger prism so that a fingerprint image can be propagated therefrom; a camera mounted within the portable apparatus so as to be capable of receiving fingerprint images propagated from the finger prism and a recording component for capturing the received fingerprint images; image capturing means for obtaining an image of the person being fingerprinted; display means for viewing an image from a group of images including the fingerprinted persons image and the captured fingerprint image; and terminal means, connected to the fingerprint scanner, image capturing and display means, for selecting the image to be viewed; a base unit connected to the terminal means, for receiving the selected image, and operative in digitizing the selected image wherein the portable image collection unit is selectively removable from the base unit. the terminal means comprise transmission means for transmission of the fingerprinted persons image and the captured fingerprint images to the base unit means. the transmission means comprise means for wireless transmission of the fingerprinted persons image and the captured fingerprint images. the transmission means comprise a tether cable having separate power and data lines. Data from Google Patents on Digital Fingerprinting The Comparative table for the data could be given as follows: Table 3 – Comparative analysis Patent I Patent II Description fingerprint identification system from a gray scale image of the fingerprint and the steps include converting fingerprint image into digitized gray scale image portable and lightweight fingerprint scanning apparatus which can optically scan and record fingerprint images in the field and transmit these images to a mobile unit for processing Process generates a gradient map of the fingerprint image and defines a calculation kernel over which ridge angle determination is made a fingerprint scanner for capturing a fingerprint image of the individual, a camera for capturing a photographic image of a person or a scene and means for transmitting the fingerprint image and the photographic image to a mobile unit Functions converting a fingerprint image into a digitized gray scale image comprising a plurality of individual pixels; enhancing the gray scale to provide a uniform contrast over the entire fingerprint image; and down-sampling the contrast enhanced image to limit the number of pixels to be analyzed; determining the ridge angle and image quality of the fingerprint image smoothing the Ridge Angle Map and the image quality map. smoothing the Ridge Angle Map is performed by the process of erosion and dilation. smoothing the image quality map is performed by the process of Fourier filtering. image capturing means for obtaining an image of the person being fingerprinted; display means for viewing an image from a group of images including the fingerprinted persons image and the captured fingerprint image; and terminal means, connected to the fingerprint scanner, image capturing and display means, for selecting the image to be viewed; the terminal means comprise transmission means for transmission of the fingerprinted persons image and the captured fingerprint images to the base unit means. the transmission means comprise means for wireless transmission of the fingerprinted persons image and the captured fingerprint images. (Ort et al, 1997/2009 and Fishbine et al 1995/2009) Chapter V: Discussion, Conclusions, and Recommendations The differences in fingerprinting technology are studied with special emphasis on the methods or techniques of obtaining, storing and accessing information and images that could enhance the purpose of digital fingerprinting in forensic science. The results obtained bring out a comparative analysis of the two equipment that have been patented for digital fingerprinting and the first equipment represents capturing the image and using it in a contrasting background so that ridges and other peculiarities are easily deciphered. So the first patent is about imaging of fingerprints and enhancing the images that could further help in classification and storage of data (Ort et al, 1997/2009). The second patent is about scanning and transmission of scanned data that could be used for processing of information and comparisons of already stored data and the evidence available (Fishbine et al, 1995/2009). Both the patents enhance functionality, one by improving the quality of image and the other by improving the quality of transmission. The first equipment helps in enhanced qualitative analysis of the fingerprints obtained making images more detailed, accurate and specific. The second equipment is more important for its functions as it improves the general process of digital fingerprinting. Thus when the first kind of equipment deals with the structural enhancement of fingerprinting by making the imaging more accurate and reliable, the second equipment as in patent II improves the overall functionality of the imaging system as data could be immediately transmitted, recorded and stored and compared with other available images (Fishbine et al, 1995/2009). So when the first patent is about improving structure and imaging, the second patent improves functions and processing. The two patents discussed here seem to have complementary rather than competitive features so both could be used in digital fingerprinting not just to enhance images that would provide remarkable accuracy to the finest ridges and patterns using grey scale imaging technique, but also enhance functionalities of digital fingerprinting by improving accessibility, processing and transmission. In conclusion it could be said that the study shed light on the applicability of digital fingerprinting methods and techniques and highlights the importance of functionalities and processes in making such techniques more efficient. The literature review and introduction of this research paper focused on the methods of digital fingerprinting and its uses and applicability to control crime. With the use of enhanced grey scale technology as the patent equipment discussed here entails, digital fingerprinting could reach advanced levels of accuracy that would help in the precision of images and imaging techniques that could store the most detailed and accurate images as grey scale imaging helps to identify ridges, singularities and patterns better than other techniques. The precision of the images would mean that fewer distorted images will be entered into the database and this will make the categorization of fingerprints highly efficient as well. The second technique deals with using scanning and transmission devices to transmit images to a mobile or wireless unit that could instantly compare the image obtained with the images stored in a large database so the individual whose fingerprints are scanned is easily identified (Fishbine, et al. 1995/2009). This process is useful for identification of criminals whose details are already available and stored in a database so matching fingerprints would mean easy identification of the individual. DNA fingerprinting and imaging techniques are used successfully in crime investigations including theft, rape and murder and data stored as fingerprint images are very useful in identifying established or known criminals. The sort of evidence is however also useful in general situations when employees of an organization need access to restricted area and fingerprint scanning could identify the individual and help provide access through an automated system. The fingerprinting technology and matching acts as an automated identification device and could be used not just to locate criminals but also to provide access at border points, restricted job areas and in secured spaces (Lofvenberg, 2001). Digital fingerprinting technology is advancement in itself and advancing further to enhance the use of the technology should thus be encouraged to improve the applications of the devices in forensic sciences. This thesis which highlights the functional and structural aspects of fingerprinting by considering issues such as assessment, accessibility, precision, identification highlights the fact that digital fingerprinting largely relies on advances in technology to improve its structural and functional capabilities and whether it is to enhance identification processes or to control crime, digital fingerprinting could be one of the most effective methods in forensic sciences. Digital fingerprinting is reaching more advanced levels of technological changes and the two patents and techniques discussed here show that the fingerprinting methods are changing rapidly making the methods more accessible and accurate to lessen the amount of distorted images and to enhance the efficiency of the fingerprinting process in forensic studies. Recommendations could thus be made that both these devices could be appropriate for the enhancement of digital fingerprinting and could be incorporated in the applications of fingerprinting techniques within the forensic departments that deal with fingerprints, data storage and imaging. References Alon N.; Cohen G.; Krivelevich M.; Litsyn S. (2003) Generalized hashing and parent-identifying codes.Journal of Combinatorial Theory, Series A, Volume 104, Number 1, pp. 207-215(9) Bond, John W. (2008) The Thermodynamics of Latent Fingerprint Corrosion of Metal Elements and Alloys. Journal of Forensic Sciences, Volume 53, Number 6, pp. 1344-1352(9) Casey E (2000) Digital Evidence and Computer Crime: Forensic Science, Computers, and the Internet with Cdrom, 1st edition.Academic Press, Inc.  Crawford, J.T. (2003) Genotyping in contact investigations: a CDC perspective. The International Journal of Tuberculosis and Lung Disease, Volume 7, Supplement 3, pp. S453-S457(1) Chang, M-C.; Lou, D-C.; Tso, H-K. (2007) Combined watermarking and fingerprinting technologies for digital image copyright protection. Imaging Science Journal, The, Volume 55, Number 1, pp. 3-12(10) de Vries, Gerard; van Hest, Rob A. (2006) From contact investigation to tuberculosis screening of drug addicts and homeless persons in Rotterdam. European Journal of Public Health, Volume 16, Number 2, pp. 133-136(4) Emmanuel, Sabu; Kankanhalli, Mohan. (2006) Mask-based fingerprinting scheme for digital video broadcasting. Multimedia Tools and Applications, Volume 31, Number 2, pp. 145-170(26) Fishbine Glenn M., Withoff Klein Robert J., Theodore D. (1995) Portable fingerprint scanning apparatus for identification verification Digital Biometrics, Inc. accessed 2009.Google Patents - Digital Fingerprinting http://www.google.com/patents?id=3Z8eAAAAEBAJ&dq=digital+fingerp rinting+crime Gomes L.d.C.T.; Cano P.; Gómez E.; Bonnet M.; Batlle E. (2003) Audio Watermarking and Fingerprinting: For Which Applications? Journal of New Music Research, Volume 32, Number 1, pp. 65-81(17) Jain Anil K., Prabhakar Salil, Lin Hong (1999) A Multichannel Approach to Fingerprint Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence .Volume 21 ,  Issue 4  (April 1999) Pages: 348 - 359   Judge P.; Ammar M. (2002) WHIM: watermarking multicast video with a hierarchy of intermediaries. Computer Networks, Volume 39, Number 6, pp. 699-712(14) Katyal Neal Kumar (2003) Digital Architecture as Crime Control.Yale Law Journal, Vol. 112 Kinjo M.; Nishimura G. (1996) Analysis of the number of DNA fragments in solution using fluorescence correlation spectroscopy. Progress in Biophysics and Molecular Biology, Volume 65, Supplement 1, pp. 197- 197(1) Kirby, Lorne T. (1990) DNA fingerprinting : an introduction / Lorne T. Kirby.New York, N.Y. : Stockton Press. Lian, S.G. (2009) Secure image distribution based on joint decryption and fingerprinting. Imaging Science Journal, The, Volume 57, Number 2, pp. 84-93(10) Liu Manhua Xudong Jiang Alex Chichung Kot(January 2005) EURASIP Journal on Applied Signal Processing Volume 2005 ,   498 - 509  . Paterson, Maura. (2007) Sequential and dynamic frameproof codes. Designs, Codes and Cryptography, Volume 42, Number 3, pp. 317-326(10) Mardia K. V.; Coombes A.; Kirkbride J.; Linney A.; Bowie J. L. (1996), On statistical problems with face identification from photographs. Journal of Applied Statistics, Volume 23, Number 6, pp. 655-676(22) Mertens, Ralf; Allen, John J.B.The role of psychophysiology in forensic assessments: Deception detection, ERPs, and virtual reality mock crime scenarios. Psychophysiology, Volume 45, Number 2, March 2008 , pp. 286-298(13) Naik G. (1995) Cellular carriers try new tricks to beat bandits. Computers and Security, Volume 14, Number 2, pp. 119-119(1) Nelkin, Dorothy; Andrews, Lori. (1999) DNA identification and surveillance creep. Sociology of Health & Illness, Volume 21, Number 5, pp. 689- 706(18) Ort James R., Lange Douglas L., Kiefer Frederick W., Dennison Raymond J. (1997) Fingerprint identification system - Calspan Corporation – Google Patent, accessed 2009 http://www.google.com/patents?id=bdIXAAAAEBAJ&dq=digital+fingerpr inting+crime Löfvenberg, Jacob.(2001) Codes for digital fingerprinting / Jacob Löfvenberg.Linkoping studies in science and technology -dissertations- ; no 722. Linköping : Department of Electrical Engineering, Linköping University. National Research Council (U.S.). (1992) Committee on DNA Technology in Forensic Science. DNA technology in forensic science / Committee on DNA Technology in Forensic Science, Board on Biology, Commission on Life Sciences, National Research Council. Washington, D.C. : National Academy Press. Qinzhi Zhang,Kai Huang,Hong Yan (2001)Fingerprint classification based on extraction and analysis of singularities and pseudoridges. ACM International Conference Proceeding Series; Vol. 147. Proceedings of the Pan-Sydney area workshop on Visual information processing - Volume 11 .Pages: 83 – 87. Australian Computer Society, Inc. Ratha, N.K.   Karu, K.   Shaoyun Chen   Jain, A.K (1996/2006). A real-time matching system for large fingerprint databases.Pattern Analysis and Machine Intelligence, IEEE Transactions.Volume: 18,  Issue: 8.: 799-813 Shie, S.C.; Lin, S.D.; Jiang, J.H. (2008) Image steganographic scheme using predictive side match vector quantisation. Imaging Science Journal, The, Volume 56, Number 3, June pp. 123-135(13) Song, Yun S.; Patil, Anand; Murphy, Erin E.; Slatkin, Montgomery. (2009), Average Probability that a “Cold Hit” in a DNA Database Search Results in an Erroneous Attribution. Journal of Forensic Sciences, Volume 54, Number 1, pp. 22-27(6) Suggs J.A.; Beam E.W.; Biggs D.E.; Collins W.; Dusenbury M.R.; MacLeish P.P.; Nottingham K.E.; Smith D.J.(2002) Guidelines and Resources for Conducting an Environmental Crime Investigation in the United States. Environmental Forensics, Volume 3, Number 2, pp. 91-113(23) Stinson D.R.; van Trung T.; Wei R. (2000) Secure frameproof codes, key distribution patterns, group testing algorithms and related structures. Journal of Statistical Planning and Inference, Volume 86, Number 2, pp. 595-617(23) van der Ploeg I. (1999) The illegal body: `Eurodac and the politics of biometric identification.Ethics and Information Technology, Volume 1, Number 4, pp. 295-302(8)   Read More