Objective detection of shear distortion of low-light-level image intensifier based on global scanning and image patch edge feature analysis

Shear distortion is the defect brought in the manufacturing stage of optical fiber panel of low-light-level (LLL) image intensifier. The traditional detection method of such defects is purely based on visual observation, so the recording measure is rough and the amount of manual intervention is large. According to the above facts, an objective detection method of shear distortion of LLL image intensifier based on global scanning and image patch edge feature analysis is proposed. Firstly, the inclination of parallel lines is calculated to realize the normalized rotation of the target image; Then, the effective area is scanned globally by means of spatial kernel for local defect detection. The image in the kernel is processed to retain only the edge features, and then the proposed shear distortion detection strategy is applied to each edge in the processed image. Finally, the distortion points in the local image are restored to the target image through the image patch spatial coordinates. To substantiate the performance of the proposed method, a series of image tubes with diverse degrees of shear distortion are put into experiments, and the relevant detection technologies are used as the comparison. It yields the conclusion that the proposed method is robust to the background noise, illumination change and image defects to some extent, and is superior to the relevant detection technology in overall performance. Compared with the traditional visual inspection method, this method not only standardizes the recording measure of test results, but also has better time stability.