DocumentCode :
736770
Title :
A Novel Defect Inspection Approach Using Image Processing and Support Vector Machines in Bolts
Author :
Lv, Xiao
fYear :
2015
fDate :
13-14 June 2015
Firstpage :
40
Lastpage :
43
Abstract :
To get rid of the weaknesses of the traditional defect inspection of the bolts, such as low efficiency, high cost, and poor-feasibility, a novel inspection approach for bolt looseness inspection based on the image processing technology using the charge coupled device (CCD) as the image sensor and the support vector machine (SVM) was proposed. The digital image of the tested bolt was collected by a DS-2AE7162-A CCD digital camera and input into computer by an image acquisition device. The original digital image with noise was processed by Gaussian filter and histogram equation to reduce its noise, and located by YCbCr color space. The samples feature descriptions of the bolts were extracted. A linear classifier model for defect inspection which based on the SVM was proposed. Experiments on several datasets demonstrate our approach is characterized by low cost, high efficiency, and easy realized.
Keywords :
Classification algorithms; Fasteners; Feature extraction; Image color analysis; Inspection; Mathematical model; Support vector machines; Bolt; Defect Inspection; Image Processing; Support Vector Machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Measuring Technology and Mechatronics Automation (ICMTMA), 2015 Seventh International Conference on
Conference_Location :
Nanchang, China
Print_ISBN :
978-1-4673-7142-1
Type :
conf
DOI :
10.1109/ICMTMA.2015.46
Filename :
7263509
Link To Document :
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