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| Fabric Defect Detection Based on Similarity Relation |
| LIANG Jiuzhen, GU Chengxi, CHANG Xingzhi |
| School of Information Science and Engineering, Changzhou University, Changzhou 213164 |
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Abstract Focusing on the fabric defect detection with periodic variation pattern, a fabric defect detection method based on similarity relation is proposed. Firstly, the size of the periodic model is conformed. Secondly, grounded on the equivalence class partition method, block clustering is performed according to the cycle size (template). Then, the defect blocks are located. The similarity relation between blocks is transformed into equivalence relation and a threshold segmentation strategy is put forward. Finally, the defect detection method based on neighborhood information is added to complete the detection process. Experiments show that by the proposed method the detection accuracy is improved substantially, and the detection process is simpler and more practical.
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Received: 04 January 2017
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About author:: (LIANG Jiuzhen(Corresponding author), born in 1968, Ph.D., professor. His research interests include computer vision.)
(GU Chengxi, born in 1994, master student. His research interests include computer vision.)
(Chang Xingzhi, born in 1979, Ph.D., associate professor. His research interests include computer vision.) |
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2017, Vol. 30 
