Location and Correction of Geometrically Transformed QR Code Images - Essay Example

QR al Affiliation) A QR is a bar with two-dimensional that performs information encoding. An acceptable QR code has only white and black squares, and thus seems unattractive. The paper develops a novel benchmark to embellish the standard QR code thus making it recognizable and attractive by any user while maintaining the scalability. The proposed mechanism is inspired by the methods of artistic. A QR code is conventionally embellished the by decorating the squares and then embed the images onto it. In the proposed work, the squares are reshaped with the help of binary exemplar by making the local appearances to resemble the illustrated shape. In addition, the technique for error-aware warping from deformation of the embedded image is built. It reduces the QR code that is brought through embedment of the image to maximize the code’s readability (Roebuck, 2011). The proposed algorithm has lower data error than the global transformation found in the previous since the warping can domestically deform the image in conforming the squares surrounding it. The proposed benchmark was looked, evaluated, and analyzed by using it in embellishing the extensive QR codes collection and in testing the readability with a variety of the commercial readers of QR codes (“Information technology - automatic identification and data capture techniques - QR Code 2005 bar code symbology specification = Technologies de information - techniques identification automatique et de capture des données - spécification de la symbo”, 2000). Introduction Quick Response Code is a barcode with two dimensional used in encoding information. The code is popular and used widely because of lower cost in creating it, large capacity for storing data, and very fisrrt readability. The users of smartphones can use the decoded information in the camera in reading the QR cpdes in any media including the monitors and the magazines. The QR code is the popuar instrument the companies and brand marketing have been used in advertising (Waters, 2012). Despite the QR codes are found everywhere, they are developed to be used by the machines only. The standard code has the black and water squares that are pixelated. The encode information can never be comprehended with the reader of the QR code. The eye is not attractive when displayed or printed in the advertising media like the billboards, posters, and business cards. Of late, some of the developed had design the codes in an attractive manner in order to be recognized without the readability reduction. The codes are basically colored with various shapes. They also have images that make the information to be more visible (Blake, 2011). The embellishment of the QR code is much challenging than the production of the standard one since the process destroys the information that is encoded. The good thing is that, the data error and data loss in QR code can be tolerable and correctable and the properties of the correction. Therefore, embellishing the QR code, the expertise normally performs the process of error and trial, which the readability level is evaluated when the QR codes are modifies. The QR code can be made recognizable and attractive by embedding the images in the QR cods and stylizing the white and black images. The goal of the paper facilitates the processes, and thus facilitating the QR code embellishment (“Specification for QR code”, 2008). Proposed Approach The most crucial feature of the tasks was deformation of the embedded images to reduce the code error for the QR. Additional task was to stylize the task in reference to the specified illustration during the QR code maintenance. The two task were ensured through coming up with a framework bearing the two characteristics; module stylization and image embedding. The task of image embedding deformed the input image in reducing the caused error for the QR. Based on the observation; the work built the image of code aware that reforms the input image in minimizing the code error of QR. The input image is projected into a mesh that is triangular and the mesh that is optimally deformed. The method of local deformation minimizes the code error for QR more than the impact of the global information that entails translation, rotation, and scaling. The component of the model stylization reshapes the model in a way that is determined by the shapes of the input. Specifically, the aim of the component is synthesing the modules new shape that will look like the illustration of the style (Sansweet, 2011). Timeline The aim of the module stylization is module reshaping according the illustrated shape of the unit, so that the task has the same appearance as the shape. Additionally, the stylized modules need to resemble the previous square shapes in reducing the error code for the QR. Since the shape can undergo representation as the binary image, it is assumed that the exemplary image is represented (Fritton, 2011). The method synthesis the modules of QR code style which assumes the example. To attain this, one uses a simple way of adopting the method of texture synthesis. However, the method could cause the error for the QR code since they have no control on the boundary. Rather, we build a boundary synthesis which tends to synthesis the modules stylized boundaries. The technique is efficient since the search space is confined to the pixel’s boundary and the same metric only counts for the boundary pixel’s contributions rather than the pixel in the local window. The graph below shows the similarity metric for the boundary patch. The similarity between double boundary patches N (pm) and N (pe) is the summation of the distance from a single patch to another. The boundary synthesis technique starts by representing the exemplar and modules of QR code using the boundary pixels. The pixels correspondence is decided by parameterizing the borders while aligning the central pixels pm and pe and match proportionally the boundary pixels. The stylization for the module QR code is efficient. The total time for the execution is 24ms. The computational time of the code aware non-uniform warping is dependent on the vertices’ number. The convergence will take around five to minutes since the process of optimization entails iterative texture mapping. Risk Assessment . The process of readability is tested using the QR readers such as i-nigma, Scan MyDoc, Scan, and others. The scanning possesses a large threat to the user’s health wise. Scanning using the QR cods scan exposes the users to cancerous diseases which can easily to patients deform, and later death. Therefore, using the computer during the scanning puts the user in various health risks. One health issue that normally occurs from using the computer for a long period of time is straining of the eye. This is normally arises by looking at the monitor which is positioned at a constant distance from the screen. The muscles used in focusing the eye are not moved, so they tend to get painful and tired. This straining of the eye causes headaches to the user. Additionally, a lot of people suffer from the neck pain and back from working with the computer for a long period of time. This is normally associated with poor sitting posture. Additionally, there is repetitive strain injuries found in hands and wrists. Any movements that are repetitive result in health problems termed as the repetitive strain injury. To be specific, typing and using mouse for a longer period of time cause the repetitive Strain injury on the wrist. (“Information technology - automatic identification and data capture techniques - QR Code”, 2005). Progress to Date The proposed benchmark was helpful in embellishing the various QR codes. The exemplars and the images found on the left were used effectively in decorating the codes while reducing the error. The input images sizes were found to be 400 by 400 while the symbols were found to be 700 by 700. To minimize the errors that is created by the embellishment of the images darker parts need to be fitted into the dark modules. Thus, the body and the head of the meriolion in diagram 1 and the main body of people in diagram 10 are squashed slightly to conform the shape of the dark mode=les and the snakes shape in diagram 1. Diagram is a glass that is stretched in fitting into the dark modules. At times, the uniform scaling is present in reducing the error. Diagram 1 presents the illustration, where there is slight alteration, effectively maintaining the readability and image visual appeal. The work in progress involves users imposing distortion that corresponding to some regions that need distortion. The work compares the code word level effectiveness and the error terms that are in module level. The embedded panda are warped with all the error levels (Franke, 1971). Additionally, the results are compared under the global transformation, the embedded images undergoes a larger rotation and transformation that is not attractive to the users. The progress involves allowing the images to undergo the deformation as shown in diagram 12. The module stylization for the QR code is efficient, Conclusion Embellishing the QR code, the expertise normally performs the process of error and trial, which the readability level is evaluated when the QR codes are modifies. The QR code can be made recognizable and attractive by embedding the images in the QR cods and stylizing the white and black images. The proposed benchmark was helpful in embellishing the various QR codes. The exemplars and the images found on the left were used effectively in decorating the codes while reducing the error. The input images sizes were found to be 400 by 400 while the symbols were found to be 700 by 700. To minimize the errors that is created by the embellishment of the images darker parts need to be fitted into the dark modules. Additionally, the method synthesis the modules of QR code style which assumes the example (Newman & Sproull, 1979). To attain this, one uses a simple way of adopting the method of texture synthesis. However, the method could cause the error for the QR code since they have no control on the boundary. Rather, we build a boundary synthesis which tends to synthesis the modules stylized boundaries. The technique is efficient since the search space is confined to the pixel’s boundary and the same metric only counts for the boundary pixel’s contributions rather than the pixel in the local window. References Blake, S. (2011). QR code Amy Goodman: flipbook. Omaha, NE: Scott Blake. Franke, H. W. (1971). Computer graphics, computer art. London: Phaidon. Fritton, C. (2011). QR code book: why we lose our hands. Buffalo: Ferrum Wheel Press. Information technology - automatic identification and data capture techniques - QR Code 2005 bar code symbology specification = Technologies de linformation - techniques didentification automatique et de capture des données - spécification de la symbo (2nd ed.). (2006). Geneve: ISO/IEC. Information technology -- automatic identification and data capture techniques -- bar code symbology -- QR code = Technologies de linformation -- techniques didentification automatique et de capture de données -- symboles de codes à barres -- code QR.. (2000). Geneva: ISO :. Newman, W. M., & Sproull, R. F. (1979). Principles of interactive computer graphics (2d ed.). New York: McGraw-Hill. Roebuck, K. (2011). QR code: high-impact strategies : what you need to know : definitions, adoptions, impact, benefits, maturity, vendors. Place of publication not identified: [publisher not identified]. Sansweet, J. (2011). Introducing the QR code: the reality & the magic. Auckland, N.Z.: ProofreadNZ Ltd. Specification for QR code. (2008). Singapore: SPRING Singapore. Waters, J. (2012). QR codes for dummies portable edition. Hoboken: John Wiley & Sons. Appendix: Algorithms Diagrams Read More