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Journal of Sensors - Volume 2016 2016, Article ID 5479152, 8 pages -

Research Article

School of Measurement-Control Tech and Communications Engineering, Harbin University of Science and Technology, Harbin 150080, China

College of Automation, Harbin Engineering University, Harbin 150001, China

Received 5 January 2015; Accepted 26 February 2015

Academic Editor: Yong Zhang

Copyright © 2016 Xiaoyang Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


To achieve automatic sorting on commodity trademarks, a binocular vision system has been constructed in this paper. By adjusting camera pose, this system can obtain greater shooting perspective. In order to improve sorting accuracy, a now SGH recognition method is proposed. SGH consists of spatial color histogram S feature, gray level cooccurrence matrix G feature, and Hu moments H feature, which represent color feature, texture feature, and shaper feature, respectively. Similarity judgment function is built by using SGH. The experimental results show that SGH algorithm has a higher visual accuracy compared to single feature based recognition method.

Autor: Xiaoyang Yu, Shuang Liu, Ming Pang, Jixun Zhang, and Shuchun Yu



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