부산대학교 도서관

This paper proposes a new approach for the defect classification of electronic board using Bag of Keypoints and SVM. The main purpose of this paper is not to use the reference image which can be used to extract the difference region of defect. The approach represents histogram features of Bag of keypoints based on extracting features from data set images. Feature vectors are used for SVM learning and classification. The effectiveness of the approach is evaluated with accuracy of defect classification for images with actual defects in comparison with the previously proposed approaches.