Complicated intermittent scratches detection research on surface of optical components based on adaptive sector scanning algorithm cascading mean variance threshold algorithm

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

doi:10.1117/12.2511381

7 March 2019 Complicated intermittent scratches detection research on surface of optical components based on adaptive sector scanning algorithm cascading mean variance threshold algorithm

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

Author Affiliations +

Proceedings Volume 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation; 110531L (2019) https://doi.org/10.1117/12.2511381
Event: 10th International Symposium on Precision Engineering Measurements and Instrumentation (ISPEMI 2018), 2018, Kunming, China

Abstract

In inertial confinement fusion system, the intermittent scratches on the polished surface of single-sided polished and bottom surface frosted optical components are complex, and it’s of great difficulty to extract them completely. In order to solve this problem, established in the light-field surface detection system, this paper brings forward a novel intermittent scratch detection method based on adaptive sector scanning algorithm (ASC) cascading mean variance threshold algorithm (MVTH). In the preprocessing step, dividing the original image into subimages with a number of integer multiple of cpu cores so as to fully compress image processing time utilizing parallel processing, using mean filter to balance background and then obtaining binary subimages utilizing morphology and threshold operations, finally, utilizing Two-pass algorithm to label the connected domains of binary subimages. In the detection step, considering the complexity of the pattern of intermittent scratches, ASC is first used for routine intermittent scratches stitching and then supplemented by MVTH. In the verification step, in order to prove that the detected intermittent scratches satisfy the criteria for scratches in human eyes, the method of support vector machine (SVM) pattern recognition is utilized to compare the detected results with the continuous scratch samples detected by human eyes. This algorithm has high degree of parallelism, high speed and strong robustness. The experimental results illustrate that the complete extraction rate of intermittent scratches is 93.59% , the average processing time of single image is merely 0.029 second and the accuracy rate of detection is up to 98.72% by SVM verification.

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Fanyi Wang, Pin Cao, Yongying Yang, Rongzhi Liu, Fan Wu, Pengfei Zhang, Jiabin Jiang, Huiting Chai, Yihui Zhang, Yubin Du, Guohua Feng, Xiang Xiao, and Yanwei Li "Complicated intermittent scratches detection research on surface of optical components based on adaptive sector scanning algorithm cascading mean variance threshold algorithm", Proc. SPIE 11053, Tenth International Symposium on Precision Engineering Measurements and Instrumentation, 110531L (7 March 2019); https://doi.org/10.1117/12.2511381

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