A defect detection method based on sub-image statistical feature for texture surface

Xiaojun Wu; Huijiang Xiong; Peizhi Wen

doi:10.1117/12.2244917

29 August 2016 A defect detection method based on sub-image statistical feature for texture surface

Xiaojun Wu, Huijiang Xiong, Peizhi Wen

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100333Y (2016) https://doi.org/10.1117/12.2244917
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

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.

Citation Download Citation

Xiaojun Wu, Huijiang Xiong, and Peizhi Wen "A defect detection method based on sub-image statistical feature for texture surface", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100333Y (29 August 2016); https://doi.org/10.1117/12.2244917

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