基于边缘引导的纺织品纹样数字化修复方法  

Digitized restoration of textile pattern through edge-guided image inpainting method

作　　者：张婧 辛斌杰[1] 袁智杰 许颖琦[1] ZHANG Jing;XIN Binjie;YUAN Zhijie;XU Yingqi(School of Textiles and Fashion,Shanghai University of Engineering Science,Shanghai 201620,China)

机构地区：[1]上海工程技术大学纺织服装学院,上海201620

出　　处：《纺织学报》2024年第2期101-111,共11页Journal of Textile Research

基　　金：国家自然科学基金项目(61876106);上海地方能力建设资助项目(19030501200);上海市Ⅲ类高峰学科-材料科学与工程(高能束智能加工与绿色制造)项目(沪教委科[2018]43号)

摘　　要：针对破损纺织品文物人工修复周期长、易造成二次破坏等问题,提出一种用改进的Criminisi算法修复破损传统纺织品纹样的数字化方法。该算法通过对缺失边缘进行重构还原纺织品纹样的结构,用于引导进一步的纹理修复。首先使用线性或二阶贝塞尔曲线拟合缺失边缘,以恢复结构;然后利用多分辨率图像中的结构信息计算更有效的优先权,确定当前待修复块;再在多分辨率图像中根据颜色、梯度和边界特征计算多个候选匹配块,从中选择最佳匹配块以减少选择过程中的随机性;最后通过分割复制的最佳匹配块进行填补,以减少对已知信息区域的覆盖,迭代完成全部破损区域的修复。实验结果表明,本文算法对存在较多结构破坏的真实纺织品彩色图像可快速实现较为自然的修复效果。Objective This study aims to further improve the Criminisi algorithm to effectively restore traditional Chinese textile patterns in the presence of damage.Given the complex nature of these patterns,structural restoration is essential to ensure their accurate recovery.Efforts will be directed towards improving the inpainting algorithm's performance and expanding its applicability in practical textile restoration work,with the aim of achieving faster and more accurate repair results.Our research aims to provide more feasible solutions for the preservation of cultural heritage and textile restoration,ensuring the enduring legacy of traditional Chinese textile patterns.Method Firstly,it uses linear or second-order B zier curves to fit the missing edges and restore the structure.Then,it calculates more effective priority using structural information from a multi-resolution image to determine the current patch to be repaired.Next,it computes multiple candidates matching patches in the multi-resolution image based on color,gradient,and boundary features,selecting the best-matched patch to reduce randomness in the selection process.Finally,the replicated best-matched patch is segmented before being used for filling the damaged area,reducing the overlap with known information regions and achieving iterative completion of the restoration for all damaged areas.Results Real traditional textile images were collected,and artificial damage was introduced by adding masks to simulate challenges encountered when dealing with damaged textiles.The effectiveness of the proposed algorithm was evaluated using a variety of objective metrics,including the peak signal-to-noise ratio,structural similarity feature similarity index measure,feature similarity index measure,and edge preservation rate.These metrics provided a comprehensive and quantifiable assessment of the restoration results.Apart from the quantitative assessments,a subjective evaluation of the inpainting results was also carried out.This qualitative assessment revealed that

关 键 词：纺织品 文物修复 图像修复 多分辨率图像 结构信息 

分 类 号：TS941.26[轻工技术与工程—服装设计与工程] G264.3[历史地理—考古学及博物馆学]