Imaging Components, Systems, and Processing

Using computer vision and compressed sensing for wood plate surface detection

[+] Author Affiliations
Yizhuo Zhang, Sijia Liu, Wenjun Tu, Huiling Yu, Chao Li

Northeast Forestry University, No. 26 Hexing Road, Xiangfang District, Harbin 150040, China

Opt. Eng. 54(10), 103102 (Oct 12, 2015). doi:10.1117/1.OE.54.10.103102
History: Received May 7, 2015; Accepted August 19, 2015
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Abstract.  Aiming at detecting the random and complicated characteristic of wood surface, we proposed a comprehensive detection algorithm based on computer vision and compressed sensing. First, integral projection method was used to trace and locate the position of a wood plate; then surface images were obtained by blocks. Second, multiscaled features were extracted from image to express the surface characteristic. Third, particle swarm optimization algorithm was used for multiscaled features selection. Finally, the defects and textures were detected by compressed sensing classifier. Five types of wood samples, including radial texture, tangential texture, wormhole, live knot, and dead knot, were used for tests, and the average classification accuracy was 94.7%.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Yizhuo Zhang ; Sijia Liu ; Wenjun Tu ; Huiling Yu and Chao Li
"Using computer vision and compressed sensing for wood plate surface detection", Opt. Eng. 54(10), 103102 (Oct 12, 2015). ; http://dx.doi.org/10.1117/1.OE.54.10.103102


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