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Barcode Region of Interest Extraction Method Using a Local Pixel Directions in a Multiple Barcode Region Image
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 Title & Authors
Barcode Region of Interest Extraction Method Using a Local Pixel Directions in a Multiple Barcode Region Image
Cho, Hosang; Kang, Bongsoon;
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In this paper presents a method of extracting reliable and regions of interest (ROI) in barcode for the purpose of factory automation. backgrounds are separated based on directional components and the characteristics of detected patterns. post-processing is performed on candidate images with analysis of problems caused by blur, rotation and areas of high similarity. In addition, the resizing factor is used to achieve faster calculations through image resizing. The input images contained multiple product or barcode for application to diverse automation environments; a high extraction success rate is accomplished despite the maximum shooting distance of 80 cm. Simulations involving images with various shooting distances gave an ROI detection rate of 100% and a post-processing success rate of 99.3%.
Image Processing;Region of Interest;Automatic Identification;Barcode Pattern Information;
 Cited by
N. Liu, X. Zheng, H. Sun, X. Tan, "Two-dimensional bar code outof-focus deblurring via the Increment Constrained Least Squares filter", Pattern Recognition Letters, vol. 34, no.2, pp. 124-130, Jan. 2013. crossref(new window)

H. Yang, A.C. Kot, X. Jiang, “Binarization of low-quality barcode images captured by mobile phones using local window of adaptive location and size,” IEEE Transactions on Image Processing, vol. 21, no.1, pp.418-425, Jan. 2012. crossref(new window)

M. Katona and L. G. Nyul, “A novel method for accurate and efficient barcode detection with morphological operations,” Signal Image Technology and Internet Based Systems(SITIS) 2012 Eighth International Conference on, pp. 307-314, 2012.

C. Zhang, J. Wang, S. Han, M. Yi, Z. Zhang,, “Automatic Real-Time Barcode Localization, in Complex Scenes,” IEEE International Conference on Image Processing, Atlanta, pp. 497-500, 2006.

J. P. Fang, Y. Chang, W. Chu and K. W. Chen, “Incomplete Barcode Reading Mechanism with Remote Database Access,” Recent Advances in Computer Science and Information Engineering Lecture Notes in Electrical Engineering, vol. 124, pp 705-710, 2012. crossref(new window)

H. Cho, K. Jang, C. Kim and B. Kang, “A Region of Interest Labeling Algorithm Using Three Mask Patterns,” Future Information Communication Technology and Applications, Lecture Notes in Electrical Engineering, vol. 235, pp.569-577, May. 2013. crossref(new window)

C. Sha, T. Tan, and Y. Wei, “Real-time hand tracking using a mean shift embedded particle filter,” Pattern Recognition, vol. 40, no.7, pp.1958-1970, July. 2007. crossref(new window)

H. Chu, S. Ye, Q. Guo, and X. Liu, “Object Tracking Algorithm Based on Camshift Algorithm Combinating with Difference in Frame,” Proceeding of the IEEE International Conference on Automation and Logistics, Jinan, China, pp.51-55, Aug. 2007.