Crack Detection for Metal Injection Molded Parts

MUIR > Graduate Institute of Health Care > Department of Beauty Science > Conference Papers > Item 987654321/3580

Please use this identifier to cite or link to this item: http://ir.meiho.edu.tw/ir/handle/987654321/3580

Title:	Crack Detection for Metal Injection Molded Parts
Authors:	Wang1, Hsing-Meng;Wu, Pei-Hsuan;Lee, Wen-Tzong
Keywords:	MIM;Crack Defect;Gary Level Co-Occurrence Matrix;Histogram of Oriented Gradient;Local Binary Patterns;Support Vector Machines
Date:	2018-09-03
Issue Date:	2018-09-06T03:21:18Z (UTC)
Abstract:	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.
Appears in Collections:	[Department of Beauty Science] Conference Papers

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