Defect detection method for complex surface based on human visual characteristics and feature extracting

Yubin Du; Pin Cao; Yongying Yang; Fanyi Wang; Rongzhi Liu; Fan Wu; Pengfei Zhang; Huiting Chai; Jiabin Jiang; Yihui Zhang; Guohua Feng; Xiang Xiao; Yanwei Li

doi:10.1117/12.2511490

7 March 2019 Defect detection method for complex surface based on human visual characteristics and feature extracting

Yubin Du, Pin Cao, Yongying Yang, Fanyi Wang, Rongzhi Liu, Fan Wu, Pengfei Zhang, Huiting Chai, Jiabin Jiang, Yihui Zhang, Guohua Feng, Xiang Xiao, Yanwei Li

Author Affiliations +

Proceedings Volume 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation; 110531R (2019) https://doi.org/10.1117/12.2511490
Event: 10th International Symposium on Precision Engineering Measurements and Instrumentation (ISPEMI 2018), 2018, Kunming, China

Abstract

Aimed at the problem of strong background interference introduced in digital image processing from complex surfaces under industrial defect detection, a method for complex surface defect detection based on human visual characteristics and feature extracting is proposed. Inspired by the visual attention mechanism, defect areas can be identified from the background noise conveniently by human eyes. We introduce the improved grayscale adjustment and frequency-tuned saliency algorithm combined with the salient region mask obtained by dilation and differential operation to eliminate the background noise and extract defect areas. Meanwhile the directional feature matching and merging algorithm is applied to enhance directional features and retain details of defects. Testing images are captured by our established detecting system. Experimental results show that our method can retain defect information completely and achieve considerable extracting efficiency and detecting accuracy.

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Yubin Du, Pin Cao, Yongying Yang, Fanyi Wang, Rongzhi Liu, Fan Wu, Pengfei Zhang, Huiting Chai, Jiabin Jiang, Yihui Zhang, Guohua Feng, Xiang Xiao, and Yanwei Li "Defect detection method for complex surface based on human visual characteristics and feature extracting", Proc. SPIE 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation, 110531R (7 March 2019); https://doi.org/10.1117/12.2511490

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