In the industrial quality assurance procedures, the Automatic Visual Inspection (AVI) has been widely used for various tasks, such as dimension measurement, shape distortion detection and surface damage detection. First, an AVI system for E-shaped magnetic core elements is described and a surface damage inspection algorithm is proposed in this paper. Second, the paper proposed a robust K-tSL-center clustering method to improve the accuracy, robustness and efficiency of classification. Third, the gray-scale feature (S-feature) and Gabor wavelet feature (W-feature) of the interfaces of elements are extracted to combine the SW-feature and the proposed clustering method is used to classify these interfaces into normal and damaged areas. Performance evaluations are carried out on benchmark datasets and an E-shaped magnetic core image database, in which all images are captured by the designed AVI system. Experimental results show that the proposed methods achieve an improved performance when comprising with the state-of-the-art methods in this application.