摘要： 针对物体识别中轮廓精确匹配与部位识别问题，提出一种基于最小点对成本的改进轮廓精确匹配与分析方法。采用交互式分割法学习不同类别的轮廓分析参数和轮廓原型数据，构建类别轮廓原型知识库。引入粗到精的二级匹配和最小点对成本精确匹配2种策略以进行轮廓匹配，其中粗到精的二级匹配策略可有效降低匹配过程对轮廓细节变化的敏感性，最小点对成本精确匹配策略能保证匹配具有平移不变性、旋转不变性、镜像不变性和尺度不变性，且能以直观的方式呈现匹配结果。在Animal数据集上的实验结果表明，该方法在物体识别中的部位分割、轮廓识别和部位识别等方面具有较高的准确率，且能同时精确识别轮廓类别及其部位类别。

关键词: 轮廓匹配, 最小点对成本, 精确匹配, 部位分割, 部位识别

Abstract: To realize accurate contour matching and part identification in object identification,this paper proposes an improved accurate contour matching and analysis method based on minimum point-pair cost.The method uses interactive segmentation to learn different types of contour analysis parameters and prototypes,and builds a knowledge base of class contour prototypes.Based on the prototype knowledge base,two matching strategies are introduced for contour matching:coarse-to-fine secondary matching and accurate matching with minimum point-pair cost.The former strategy can effectively reduce the sensitivity of the matching process to the changes of contour details.The latter strategy can ensure that matching is translation-invariant,rotation-invariant,mirror-invariant and scale-invariant,and can present the matching results intuitively.The experimental results on the Animal dataset show that the method has high accuracy in object identification,including part segmentation,contour identification and part identification,and can accurately identify the category of contour and its parts at the same time.

Key words: contour matching, minimum point-pair cost, accurate matching, part segmentation, part identification

中图分类号: 

• TP391