In order to effectively detect defect for fabirc image with variety of defects and complex texture, a novel fabric defect detection scheme based on textural difference-based visual saliency model was proposed, which considered the characteristics of fabric image and human visual perception. First, the test image was split into image blocks, and textural feature was extracted using LBP operator for each image block. Second, saliency was calculated by comparing their textural feature with the average texture feature. Finally, the threshold segmentation algorithm was used to localize the defect region. Comparing with the current saliency model, the proposed saliency model could effectively distinguish the defect. In addition, segmentation scheme was superior to the current defect detection algorithm in detection and localization.
; 刘洲峰; 廖亮; 赵全军; Chunlei Li
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