一种新的基于链码特征的图像检索算法  

Novel Algorithm for Image Retrieval Based on Chain Code

作　　者：孙君顶[1,2] 

机构地区：[1]河南理工大学计算机科学与技术学院,河南焦作454000 [2]苏州大学江苏省计算机信息处理技术重点实验室,江苏苏州215006

出　　处：《光电工程》2008年第9期105-109,114,共6页Opto-Electronic Engineering

基　　金：河南省教育厅自然科学基础研究基金(2007520019,2008B520012);河南理工大学博士基金(B050901);河南理工大学骨干教师资助基金;河南省基础与前沿技术研究计划项目(072300460050);苏州大学江苏省计算机信息处理技术重点实验室开放基金(KJS0715)

摘　　要：在分析采用Freeman链码进行形状描述的基础上,提出了两种链码空间分布特征的提取算法:链码分布矢量及链码相关矢量,同时对这两种方法的尺度、旋转、平移不变性进行了分析和验证;针对两种算法,分别设计了有效的相似性度量策略;最后结合链码直方图进行图像检索。由于该方法在进行图像检索时既考虑了链码的统计特征又包含了其空间分布特性,因此取得了比传统方法更好的检索效果,试验结果也证明了该算法的有效性。Based on the analysis of chain code in shape representation, two novel shape descriptors, named chain code distribution vector and chain code coherence vector, are introduced to express the spatial feature in the chain code. These two descriptors have the advantages of being invariant to the position, rotation and scaling of the image content and have nothing to do with the start point of the chain code. Combined with chain code histogram, two different matching methods are presented to measure the similarity of shape information. It is clear that both the statistical feature and the spatial feature of the chain code are considered in the new methods. Experiment results show that our methods give better performance than the traditional methods.

关 键 词：链码 空间分布特征 链码分布矢量 链码相关矢量 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]