Solving QR Code Distortions using a Recursive-based Backtracking Algorithm (original) (raw)

Color Image Coding and Decoding in QR Codes

International Journal of Science Technology & Engineering

Commonly the characters, numbers etc are embedding in QR codes. This paper introduces the concept of color image embeddings in QR codes. This is an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levelsTake one color image and converted into gray image. Then this doing the masking process, window extraction, image embedding, decoding like processes. After this process the original gray image is taken from this.

IJERT-Design and Development of QR Code Recognition from Digital Image

International Journal of Engineering Research and Technology (IJERT), 2021

https://www.ijert.org/design-and-development-of-qr-code-recognition-from-digital-image https://www.ijert.org/research/design-and-development-of-qr-code-recognition-from-digital-image-IJERTCONV9IS05039.pdf One of the most challenging topics is the recognition of qrcode recognition from image and encryption or decryption the information. The recognition of qrcode that was defines by computer or made by the computer its self using some encryption or decryption algorithm. The particular domain is the information is encrypted or decrypts information it describe particular information in secret code that contain authentication. QR code is the type of matrix barcode, which was first designed for the automotive industry by Denso Wave in Japan. The QR Code system has become admired outside the automotive industry due to its fast readability and greater storage capacity compared to standard UPC barcodes. This paper take account of QR codes basics, its real time application in day to day life and research areas associated. With the technology of mobile phones constantly emerging, especially in the area of mobile internet access, QR codes seem to be an adequate tool to quickly and efficiently converse URLs to users. This also allows offline media such as magazines, newspapers, business cards, public transport vehicles, signs, t-shirts and any other medium that can embrace the print of a QR code to be used as carriers for advertisements for online products. QR code being so versatile because of its structural flexibility that it leads to so many diverse field for research such as increasing data capacity, security applications such as different kinds of watermarking and steganography as well. Some experiments have also been done for better recognition of the QR code image that includes scratch removal techniques. Thus, this paper is an attempt to highlight some of possible research areas while considering QR codes.

Extending the Storage Capacity And Noise Reduction of a Faster QR-Code

2018

Quick Response Code has been widely used in the automatic identification fields (Liu, Ju, & Mingjun, 2008). The present work illustrates an image processing system able to discover, split and decodes the most common 2D symbol used in bar code applications. The different symbol is processed by manipulating their similarities, to achieve an integrated computational structure (Ouaviani, Pavan, Bottazzi, Brunelli, Caselli, & Guerrero, 1999). There is not enough novel approach which could be effective for data transferring to alter various sizes, a little noisy or damaged and various lighting conditions of bar code image. We proposed a faster QR code which has more storage and can scan faster. The new QR code generation takes twice the time than normal QR code but it can also store double QR code data. It's scanning is as faster as other QR code scanning technique. we deducted the level of color percentage despite positions of color bits in that module, which increased its scanning s...

QR Images: Optimized Image Embedding in QR Codes

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. The QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. To minimize the processing time, the optimization techniques proposed to consider the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Design and Development of QR Code Recognition from Digital Image

International journal of engineering research and technology, 2021

One of the most challenging topics is the recognition of qrcode recognition from image and encryption or decryption the information. The recognition of qrcode that was defines by computer or made by the computer its self using some encryption or decryption algorithm. The particular domain is the information is encrypted or decrypts information it describe particular information in secret code that contain authentication. QR code is the type of matrix barcode, which was first designed for the automotive industry by Denso Wave in Japan. The QR Code system has become admired outside the automotive industry due to its fast readability and greater storage capacity compared to standard UPC barcodes. This paper take account of QR codes basics, its real time application in day to day life and research areas associated. With the technology of mobile phones constantly emerging, especially in the area of mobile internet access, QR codes seem to be an adequate tool to quickly and efficiently converse URLs to users. This also allows offline media such as magazines, newspapers, business cards, public transport vehicles, signs, t-shirts and any other medium that can embrace the print of a QR code to be used as carriers for advertisements for online products. QR code being so versatile because of its structural flexibility that it leads to so many diverse field for research such as increasing data capacity, security applications such as different kinds of watermarking and steganography as well. Some experiments have also been done for better recognition of the QR code image that includes scratch removal techniques. Thus, this paper is an attempt to highlight some of possible research areas while considering QR codes.

Decoding Different Patterns in Various Grey Tones Incorporated in the QR Code

Acta Graphica, 2016

This paper explores the dependence of reliable decoding of grey toned QR codes on the technical characteristics of smartphone cameras marketed in the period between 2008 and 2012. The research consisted of taking a total of 12,150 QR code pictures with different grey tones, graphic patterns and error correction codes. This research answers the question whether today’s smartphones can decode such designed QR codes. The data and instructions on the quantity and size of a certain grey tone incorporated in the QR code that are sufficient to decode the researched symbology have also been given. Graphic designers can use the results of this research to make QR codes that do not drastically reduce reliability.

IEEE TRANSACTIONS ON IMAGE PROCESSING 1 QR Images: Optimized Image Embedding in QR Codes

This paper introduces the concept of QR images, an automatic method to embed QR codes into color images with bounded probability of detection error. These embeddings are compatible with standard decoding applications and can be applied to any color image with full area coverage. QR information bits are encoded into the luminance values of the image, taking advantage of the immunity of QR readers against local luminance disturbances. To mitigate the visual distortion of the QR image, the algorithm utilizes halftoning masks for the selection of modified pixels and nonlinear programming techniques to locally optimize luminance levels. A tractable model for the probability of error is developed and models of the human visual system are considered in the quality metric used to optimize the luminance levels of the QR image. In order to minimize the processing time, the optimization techniques proposed take into account the mechanics of a common binarization method and are designed to be amenable for parallel implementations. Experimental results show the graceful degradation of the decoding rate and the perceptual quality as a function the embedding parameters. A visual comparison between the proposed and existing methods is presented.

Fast Statistical Image Binarization of Colour Images for the Recognition of the QR Codes

Elektronika ir Elektrotechnika, 2015

The article concerns the fast image binarization based on the application of the statistical Monte Carlo method applied for the recognition of the QR codes from colour images, especially captured by mobile devices' cameras. Due to limited processing possibilities of some mobile devices as well as relatively low quality of some optical systems in built-in cameras, fast binarization methods are very useful for rapid recognition of the 2-D binary codes which can be found on the packages of various products and even on the street billboards. Captured images of such QR codes usually contain some background objects, may be blurred or may contain some other distortions which can hamper or make it impossible to recognize the code even considering the presence of redundant data included using Reed-Solomon's code. These problems may also occur in differing lighting conditions where the impact of binarization method and its results may be critical for further processing. The experimental results presented in the paper obtained for various colour spaces confirm the usefulness of the fast Monte Carlo based image binarization for the fast recognition of the QR codes, especially in presence of distortions and varying lighting conditions. Additionally, high performance of the Monte Carlo method allows checking different variants of binarization in order to choose the most appropriate one.

FAST MULTILAYER COLOR QR CODE DECODER ALGORITHM UTILIZING FUZZY TECHNIQUE

IAEME PUBLICATION, 2020

Color QR code is an active research topic. Most of the recent research focus on the decoding success rate and ignore the decoding speed. In this paper, we propose a fast multilayer color QR code decoder algorithm to decode an extended color QR code. The extended color QR code utilize color reference for the color recognition. The algorithm starts with the detection of the color QR code. This is followed by the calculation of the model size. Then, color reference selection from the extended QR code. Next, build a dynamic fuzzy membership, from the color reference set of the extended color QR code and fast color enhancement using the center color pixel for each model. After that, optioning monochrome color QR code by applying color de-multiplexing for the enhanced color QR code. We measure the color recovery speed and compared it with an existing work. The experiment shows using the proposed algorithm we got a decoding speed of 200% faster than the existing work..

Engineering Color Barcode Algorithms for Mobile Applications

Lecture Notes in Computer Science, 2014

The wide availability of on-board cameras in mobile devices and the increasing demand for higher capacity have recently sparked many new color barcode designs. Unfortunately, color barcodes are much more prone to errors than black and white barcodes, due to the chromatic distortions introduced in the printing and scanning process. This is a severe limitation: the higher the expected error rate, the more redundancy is needed for error correction (in order to avoid failures in barcode reading), and thus the lower the actual capacity achieved. Motivated by this, we design, engineer and experiment algorithms for decoding color barcodes with high accuracy. Besides tackling the general trade-off between error correction and data density, we address challenges that are specific to mobile scenarios and that make the problem much more complicated in practice. In particular, correcting chromatic distortions for barcode pictures taken from phone cameras appears to be a great challenge, since pictures taken from phone cameras present a very large variation in light conditions. We propose a new barcode decoding algorithm based on graph drawing methods, which is able to run in few seconds even on low-end computer architectures and to achieve nonetheless high accuracy in the recognition phase. The main idea of our algorithm is to perform color classification using force-directed graph drawing methods: barcode elements which are very close in color will attract each other, while elements that are very far will repulse each other.