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Particle detection on low contrast image of large aperture optics
Ding Wendong; Xu D(徐德); Zhang ZT(张正涛); Zhang DP(张大朋)
2016-05
Conference Name2016 Chinese Control and Decision Conference (CCDC)
Conference Date2016-5
Conference Placeyinchuan
AbstractIt's a challenge to identify actual deposited particles from the acquired optics image mixed with large noises. Due to the long working distance constraint for online inspecting large aperture optics, the vision system has great depth of view. It results in that the acquired optics image is blended with stain contamination on the back side of the inspected optics surface. In this paper, we propose a particle detection method for the low contrast image of large aperture optics. The method consists of three steps including particle candidate detection, image alignment, and particle determination. The particle candidate detection algorithm combines the gradient information to detect small particles. The actual particles are determined by the subtraction of the reference image from the inspected image with the topological information. For the detected particle, this paper also gives a classification method to identify dust and defect. Experiment shows that the actual particle on the low contract image of large aperture optics can be effectively detected and classified with the proposed method.
KeywordParticle Inspection Image Alignment Reference Image Subtraction Classification.
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19821
Collection精密感知与控制研究中心_精密感知与控制
AffiliationInstitute of automation, chinese academy of sciences
Recommended Citation
GB/T 7714
Ding Wendong,Xu D,Zhang ZT,et al. Particle detection on low contrast image of large aperture optics[C],2016.
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