Abstract:

Leather defect inspection is seriously influenced by its texture. In view that finding the defects existing in the local highlight areas of uniform change images conforms to human eye attention mechanism, we propose an automatic method for detecting leather defects based on the visual saliency model. Firstly, the features of color and brightness of the leather’s image are extracted, and then their own characteristic maps are calculated respectively by centersurround operator. Then the final saliency map is formed through merging. On this basis, the region growing method is adopted to locate the flaw detection area. In comparison with the FCM clustering segmentation, the threshold segmentation and the SVM classification, the experimental results show that the proposed method has higher precision and faster detection speed, and it can solve the problems existing in the process of leather defect detection which can be seriously affected by its texture, and be applied to automatic machine detection of leather defects.  

Key words: leather;flaw detection;saliency map;segmentation