Knowledge Management System Of Institute of optics and electronics, CAS
|Thesis Advisor||江彧 ; 毛耀|
|Place of Conferral||北京|
|Keyword||损伤在线检测 机器视觉 结构相似 Otsu 图像分割|
With the continuous irradiation of a laser, some optical components are easy to be damaged. Induced damage not only greatly increases the cost of the system, but also limits the output ability of the system. Therefore, it is necessary to detect the damage of optical components on line. When the damage of optical components was detected, the system should stop light before the damage increase sharply and deteriorate to avoid the irreversible and disastrous damage. This paper has mainly researched the online inspection method for optical components based on machine vision through extracting the feature from the image acquired by CCD to estimate the damage, and we has deeply researched the key technology of the image processing of the system.
Firstly, this paper has built an image acquisition and processing system based on the Direct-show, and the procedure and method of the video acquisition framework was narrated detailed. The image acquisition and processing software has designed, which includes image acquisition, processing, configuration, communication and other functions.
Second, this paper has studied the image similarity theory, and the damage of optical components could be inspected rapidly and in real time according to the similarity assessment of image before and after laser irradiation. The structural similarity measure algorithm (SSIM) was applied to accurately describe the optics damage degree in this paper, which has been widely used in image quality assessment.
Finally, the image segmentation algorithm has been researched for online damage inspection of optical components. Some features have been extracted from the damaged image by using image segmentation algorithm. Then we can calculate the area and major axis to analysis the optics damage degree quantitatively. However，the uneven illumination and complex damage effects in actual application may affect the result of image segmentation and damage inspection. Therefore, according to the noise characteristics of damaged image, various filtering algorithms have been researched. With the bad performance of median filter and morphology filter, the image restoration technology based on a degradation model is be used. The atmospheric scattering model has been used to approximate the degradation process of image, so the image noise can be reduced effectively by using a mean filter to estimate the degradation parameters and noise. Furthermore, in order to achieve fast and accurate segmentation, the traditional Otsu algorithm was further improved in this paper. It is the most popular image segmentation method with the advantages of easy implement and steady performance. However, its performance was decreased when some tiny object points appear in damaged image. Therefore, after getting the optimal segmentation threshold T by using the Otsu, we compute the local signal-to-noise of each pixel of the image, and search for the pixels whose gray-level is ranged at 0~T. When the local signal-to-noise of searched pixel exceeds the threshold, we use a local Otsu to segment the tiny object again.
We acquired some online damage image of the experiment to test the performance of the algorithms proposed, the experimental results verify the validity of the online damage inspection.
|陈静. 基于机器视觉的光学元件损伤在线检测研究[D]. 北京. 中国科学院大学,2017.|
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