RECOGNITION AND GENERATION OF QR/BAR CODES IN MOBILE APPLICATIONS
Journal Title: Комп’ютерне моделювання: аналіз, управління, оптимізація - Year 2019, Vol 1, Issue 1
Abstract
The article is devoted to the analysis of methods of recognition and generation of QR/bar codes in mobile applications. The most common algorithms for detecting and generating codes are considered: Otsu method, Reed-Solomon codes, binary coding algorithm, Orazio Gallo and Roberto Manduchi approach. In this article, it is proposed to use an algorithm based on these approaches, which is refined and used for the software implementation of the mobile application. The main stages of the recognition process in the work are: converting a color image into gray shades (using the pixel hue difference method); gray image binarization (Otsu algorithm); using affine transformations to preserve parallelism, which includes rotation, stretching, shifting, scaling. The main stages of the generating process for QR codes are: processing and reduction to the standard form for QR codes; the process of generating a binary string (in the work data of only numerical and symbolic types was considered); counting the total number of characters in the source string and converting the decimal number to a binary representation; determining the length of the generated binary string according to the Denso Wave standard (the encoding of character types is different); determining the required length of the final binary string; auxiliary tokens are concatenated; generation of Reed-Solomon error correction codes. Three types of bar codes are considered: code 128, code 39, and EAN 13. The last type was used. A bar code scanner includes two steps for automatically scanning all bar codes: finding the location of the bar code, bar code decoding. To localize the image and the bar code that is captured by the system, the algorithm of Orazio Gallo and Roberto Manduchi is used. In order to obtain a smoothed map, a block filter of a certain size was used, taking into account the size of the input code image. In addition to the code localization, it is cut off: the intensity of each pixel is taken into account, and the lines of the bar code (pixels with an intensity greater than zero) are highlighted. An image with improved contrast is converted to binary form, and to convert to an ideal image, each image column is scanned and checked for the maximum number of pixels with an intensity of zero or one. This article focuses on describing the edge detection process. The decoding algorithm uses an array of code width bands. All the above approaches and algorithms based on them are implemented as a mobile application for recognition and generation of codes.
Authors and Affiliations
A. N. Nikonenko, L. I. Korotka
Keywords
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- EP ID EP642564
- DOI 10.32434/2521-6406-2019-5-1-36-42
- Views 132
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