“…With the development of automation and Informa ionization, the assembly line has been transferred from manual assembly line to automatic assembly line, and the identification of the positive and negative faces of fine blanking pinion gears from manual identification to automatic identification has become an important and imminent task. In recent years, non-contact image recognition technology is widely used in the detection of the surface of the parts, Zhou Dinghe [1] used an industrial camera to obtain images of automotive plate-like painted parts, using defect extraction algorithms based on morphology Blob well classified defects identified; Wang Dongsheng [2] used machine vision technology to detect defects on rotary class toothed painted parts, for its rotary class parts size irregularities, the Developing a new inspection equipment for rotary toothed parts; Priyanka Khandelwal [5] achieved noise removal and extraction of crack defects on the surface of automotive parts by using the similar gray value filling method; Yuan Xiao Cui [4] proposed the interclass variance defect segmentation method with target variance weighting, which weights the target variance of the interclass variance of an image to ensure a high detection rate of the defects and a low misdetection rate, the Sohail Akhtar, Tatsuya Yamazaki, Jyotismita Chaki, Adarsh Tandiya, M Dhivya, BLAYVAS I, Carsten Steger and others [5][6][7][8][9][10][11][12][13][14] have done a lot of research in the detection of defects on surfaces such as circuit boards, metals, and so on, and have done a lot of research in the areas of image enhancement, region segmentation, edge extraction, Blob detection etc. many algorithms are proposed.…”