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.
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