Meiho University Institutional Repository:Item 987654321/3580
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    题名: Crack Detection for Metal Injection Molded Parts
    作者: Wang1, Hsing-Meng;Wu, Pei-Hsuan;Lee, Wen-Tzong
    关键词: MIM;Crack Defect;Gary Level Co-Occurrence Matrix;Histogram of Oriented Gradient;Local Binary Patterns;Support Vector Machines
    日期: 2018-09-03
    上传时间: 2018-09-06T03:21:18Z (UTC)
    摘要: Abstract: In the research, image processing and machine learning techniques are employed on the surface defect detection
    of metal injection molded parts. There are two sections in this manuscript; one is image capturing system, and another
    one is the machine vision inspection system. For image capturing system, the ring light with diffuser is used, and it could
    project uniform light on the metal surface. CCD cameras are used to capture the images of metal injection molded parts.
    To obtain the best quality image, the inspection system uses Sobel operator searching for the focused position where
    the sharpness measure is maximized.
    For the machine vision inspection system, local feature information of the image is extracted by Histogram of oriented
    gradient, Gary level co-occurrence matrix and Local binary patterns. The selected features are imported into the support
    vector machines classification image to classify the crack defects.
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