Abstract :
The automatic recognition algorithm of quick response code is discussed in this paper. An image processing system based on embedded system is described to be able to binarization, location, segment, and decoding the QR code. In order to adapting various sizes, various gray-level values, and under various lighting conditions of real bar code image, a high-speed, high-accuracy binarization method is developed, which can locate the finder pattern accurately and integrate the local thresholding method with global thresholding. Experiments have shown that over 99% barcode can be optimally recognized with the proposed algorithm. It can achieve higher recognition rate of high density bar code, and is applicable to real world scene image
Keywords :
Gray codes; bar codes; decoding; embedded systems; image recognition; automatic recognition algorithm; bar code image; binarization; embedded system; global thresholding; gray-level values; image processing system; local thresholding method; quick response code; real world scene image; Cameras; Code standards; Embedded system; Encoding; Error correction codes; ISO standards; Image coding; Image recognition; Information science; Mobile handsets;
