Fabric defect detection based on the saliency map construction of target-driven feature |
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Authors: | Shengqi Guan Hongyu Shi |
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Affiliation: | 1. College of Mechanical &2. Electronic Engineering, Xi’an Polytechnic University, Xi’an, China;3. College of Computer Science, Xi’an Polytechnic University, Xi’an, China |
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Abstract: | In inspection of fabric surface quality in production line, small defects have to be detected in a large background. In this paper, a new method is put forward to detect fabric surface defect by target-driven features. First of all, surface defect feature of fabric is analyzed; and then, area feature of and number feature of defects are used as tasks, which drive to enhance saliency of defective regions and to form feature saliency maps; finally, by using threshold segmentation, fusion, and filtering, fabric defect is gained from the feature saliency maps. Experiments show that the detection algorithm, compared with classic defect algorithm, can achieve accurate segmentation of the surface defects, better anti-noise ability, higher detection accuracy, which has a strong applicability on the fabric defect detection, and provides the possibility for realizing automatic detection of textile industrial product surface defect. |
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Keywords: | Fabric defect task-driven feature saliency map construction defect detection |
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