Solder Joint Inspection Using Imaginary Part of Gabor Features

Abstract

In this paper, an imaginary part of Gabor features based feature selection and classification method for electronic component solder joint inspection have been proposed. Using an image acquisition system, the images of component solder can be obtained. The RGB color solder joint image is transformed into HSI (Hue-Saturation-Intensity) model space and the image Gabor features is extracted. Then based on the algorithm of principal component analysis (PCA), feature selection is conducted. finally, the solder joint is classified using the support vector machine (SVM). The proposed inspection scheme improves efficiency and recognition, since it extracts the Gabor features and reduces the input image dimension through feature selection.