Novel segmentation algorithm for jacquard patterns based on multi-view image fusion

作     者：Wang, Wenzhen Deng, Na Xin, Binjie Wang, Yiliang Lu, Shuaigang 

作者机构：Shanghai Univ Engn Sci Sch Elect & Elect Engn Longteng Rd Shanghai Peoples R China Shanghai Univ Engn Sci Sch Text & Fash Longteng Rd Shanghai Peoples R China 

出 版 物：《IET IMAGE PROCESSING》 (IET影像处理)

年 卷 期：2020年第14卷第17期

页      面：4563-4570页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Shanghai Natural Science Foundation of China [18ZR1416600] Natural Science Foundation of China Zhihong Scholars Plan of Shanghai University of Engineering Science [2018RC03-2017] Shanghai Local Capacity Building Project of China 

主　　题：fabrics image texture image fusion image segmentation image colour analysis reverse engineering pattern image jacquard fabric cluster‐segmented complete texture information fused image calibrated image traditional unidirectional imaging method novel segmentation algorithm jacquard patterns multiview image fusion reverse engineering technology textile field textile‐pattern regeneration‐textile image segmentation algorithm segmented pattern convex pattern textures unsatisfactory pattern segmentation effect 

摘      要：Pattern regeneration is one of the applications of reverse engineering technology in the textile field, which realises the process of textile-pattern regeneration-textile, and fundamentally provides an intelligent design means of textile. At present, the method of pattern regeneration in the jacquard fabric is to use the image segmentation algorithm to segment the image digitalised by unidirectional imaging, and then the segmented pattern could be identified to regeneration for the design of new fabrics. However, due to the concave and convex pattern textures on the surface of jacquard fabric, the traditional unidirectional imaging method cannot be used for the full characterisation of its structural information, resulting in unsatisfactory pattern segmentation effect. To solve this problem, a novel segmentation algorithm for jacquard patterns based on multi-view image fusion was proposed in this study. Based on multi-view image acquisition and fusion, the pattern image of jacquard fabric could be cluster-segmented by extracting the complete texture information of the fused image and the actual colour information of the calibrated image. Compared with the traditional unidirectional imaging method, the experimental results show that the enhanced texture information of the fused image is more workable for the pattern segmentation, it validates the effectiveness of the proposed method.