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Proceedings Paper

A defect detection method based on sub-image statistical feature for texture surface
Author(s): Xiaojun Wu; Huijiang Xiong; Peizhi Wen
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Paper Abstract

Aiming at automatic visual inspection of texture surface, a texture surface defect detection method is proposed based on statistical feature of subimage. The proposed method only uses a simple image feature, gray level difference of subimage without image enhancing to detect defects on texture surface directly, avoid the feature computation of high dimension space and the learning process of large numbers of defective and defect-free similar images, which is nonsupervised detection and improving algorithm efficiency. A variety of texture surfaces from industrial manufacture materials are chosen to conduct experiments. Detection time is about few seconds and accuracy is 93.6%. Experiment results prove the proposed method can online detect various texture surface defects effectively.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100333Y (29 August 2016); doi: 10.1117/12.2244917
Show Author Affiliations
Xiaojun Wu, Harbin Institute of Technology (China)
Shenzhen Engineering Lab. of Industrial Robots and Systems (China)
Huijiang Xiong, Harbin Institute of Technology (China)
Peizhi Wen, Guilin Univ. of Electronic Technology (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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