Particle detection on low contrast image of large aperture optics

CASIA OpenIR > 中科院工业视觉智能装备工程实验室 > 精密感知与控制

	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
会议名称	2016 Chinese Control and Decision Conference (CCDC)
会议日期	2016-5
会议地点	yinchuan
摘要	It'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.
关键词	Particle Inspection Image Alignment Reference Image Subtraction Classification.
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19821
专题	中科院工业视觉智能装备工程实验室_精密感知与控制
作者单位	Institute of automation, chinese academy of sciences
第一作者单位	中国科学院自动化研究所
推荐引用方式 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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07531929.pdf（569KB）	会议论文		开放获取	CC BY-NC-SA	浏览