关键词: 疵点检测, 显著性区域特征, Gabor滤波器, 最大熵, OpenCV

Abstract: As the fabric defect type of diversity and traditional artificial detection methods inefficient ,in order to detect the fabric defect more effective, A new approach, SGE, based on saliency region feature for fabric defect detection is studied. In this approach, the original image is divided into two parts, one extracts the saliency region feature of fabric defect by improved FSR roughly, another employing the gabor filter and taking the amplitude as an output characteristics, and extracts the saliency region feature of fabric defect by PSR accurately, then by using maximum entropy to segment the saliency region respectively and fused the sub-images. The result is get got by calculating perimeter and area of the contours to removal the isolated points. The experiment selects four types of typical fabric defect images and OpenCV library is used. The experiment result shows that the algorithm, without prior learning，meet the real-time.

Key words: Defect detection, Saliency region feature, Gabor filter, Maximum entropy, OpenCV