Paper
25 August 2006 Automatic inspection of small component on loaded PCB based on SVD and SVM
Yan Wang, Yi Sun, Minghe Liu, Peng Lv, Tianjing Wu
Author Affiliations +
Abstract
Automatic inspection of small components on loaded Printed Circuit Board (PCB) is difficult due to the requirements of precision and high speed. In this paper, an automatic inspection method is presented based on Singular Value Decomposition (SVD) and Support Vector Machine (SVM). For the image of loaded PCB, we use prior location of component to get approximate region of the small component. Then the accurate numeral region of the small component can be segmented by using the projection data of this region. Next, Singular Values (SVs) of the numeral region can be obtained through SVD of the gray image. These SVs are used as the features of small component to train a SVM classifier. Then, the automatic inspection can be completed by using trained SVM classifier. The method based on projection data can overcome some difficulties of traditional method using connected domain, and reduce complexity of template matching. The SVD avoids using binary image to analyze the numerals, so the numeral information is retained as much as possible. Finally, the experimental results prove that the method in this paper is effective and feasible to some extent.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yan Wang, Yi Sun, Minghe Liu, Peng Lv, and Tianjing Wu "Automatic inspection of small component on loaded PCB based on SVD and SVM", Proc. SPIE 6315, Mathematics of Data/Image Pattern Recognition, Compression, and Encryption with Applications IX, 63150P (25 August 2006); https://doi.org/10.1117/12.678927
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Inspection

Image segmentation

Binary data

Feature extraction

Image analysis

Pattern recognition

Algorithm development

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