基于支持向量机的布匹图案匹配算法设计  

Design of fabric pattern matching algorithm based on support vector machine

作　　者：唐雪莲[1] 毕明德[1] 孙志刚[1] 

机构地区：[1]华中科技大学图像信息处理与智能控制教育部重点实验室,湖北武汉430074

出　　处：《机电工程》2011年第12期1523-1526,共4页Journal of Mechanical & Electrical Engineering

摘　　要：为了解决布匹印花过程中能够快速实现模板匹配的问题,提出了一种基于支持向量机(SVM)的匹配算法。匹配算法采用两级分类器,首先对样本布匹图像进行二值化和轮廓提取等处理得到了图像中各种图形的轮廓曲线,选择模板图形的轮廓曲线长度和面积作为简单特征量,建立了基于置信区间的分类器作为一级分类器,实现了初步匹配;然后提取模板与非模板图形轮廓曲线的傅里叶描述子,建立了基于支持向量机的分类器作为二级分类器,进行了精确匹配。研究结果表明,该算法可靠、精确、稳定,能够快速实现模板匹配,为进一步应用到工业生产中奠定了基础。In order to solve the problems of template matching with fast and accurate performance during the cloth printing process,a matching algorithm based on support vector machine（SVM） was proposed.The Otsu algorithm and contour extraction algorithms were used to acquire the contour curves of all kinds of shapes in the fabric image.The length and area of the contour curves of the template shape were calculated as simple features to build the first level classifier based on the confidence interval,which was used for coarse matching.Then the Fourier descriptors of both temple and non-template contour curves were extracted for the training of support vector machine,and a SVM classifier was built as the second level classifier for accurate matching.The experiment results show that the proposed template matching algorithm is reliable,accurate and suitable for implementation in industrial occasions.

关 键 词：傅里叶描述子 轮廓提取 模板匹配 支持向量机 

分 类 号：TH86[机械工程—仪器科学与技术] TP391.41[机械工程—精密仪器及机械]