基于相似关系的纺织品瑕疵检测方法

Fabric Defect Detection Based on Similarity Relation

针对含有周期变化图案的纺织品瑕疵检测,提出基于相似关系的纺织品瑕疵检测方法.首先确定图案的周期模板大小,然后利用等价类划分方法,针对按照周期大小分块的图像进行区块间的聚类,完成瑕疵区块的定位.将区块之间的相似关系转化为等价关系,并提出阈值分割策略.在此基础上,加入基于邻域信息的瑕疵检测方法完成检测流程.实验表明,文中方法明显提高检测效率,同时检测过程简便,容易实现.

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.