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http://bura.brunel.ac.uk/handle/2438/27749
Title: | An Efficient Bar Code Image Recognition Algorithm for Sorting System |
Authors: | Zheng, D Ran, Z Liu, Z Li, L Tian, L |
Keywords: | bar code recognition;Hough transformation;binarization;image processing |
Issue Date: | 30-Jun-2020 |
Publisher: | Tech Science Press |
Citation: | Zheng, D. et al. (2020) 'An Efficient Bar Code Image Recognition Algorithm for Sorting System', Computers, Materials & Continua, 64 (3), pp.1885 - 1895. doi: 10.32604/cmc.2020.010070. |
Abstract: | Copyright © The Authors. In the sorting system of the production line, the object movement, fixed angle of view, light intensity and other reasons lead to obscure blurred images. It results in bar code recognition rate being low and real time being poor. Aiming at the above problems, a progressive bar code compressed recognition algorithm is proposed. First, assuming that the source image is not tilted, use the direct recognition method to quickly identify the compressed source image. Failure indicates that the compression ratio is improper or the image is skewed. Then, the source image is enhanced to identify the source image directly. Finally, the inclination of the compressed image is detected by the barcode region recognition method and the source image is corrected to locate the barcode information in the barcode region recognition image. The results of multitype image experiments show that the proposed method is improved by 5+ times computational efficiency compared with the former methods, and can recognize fuzzy images better. |
URI: | https://bura.brunel.ac.uk/handle/2438/27749 https://creativecommons.org/licenses/by/4.0/ |
ISSN: | 1546-2218 |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | Copyright © The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | 494.55 kB | Adobe PDF | View/Open |
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