Image block feature vectors based on a singular-value information metric and color-texture description  

作　　者：王朔中 路兴 苏胜君 张新鹏 

机构地区：[1]School of Communication and Information Engineering, Shanghai University, Shanghai 200072, P. R. China

出　　处：《Journal of Shanghai University(English Edition)》2007年第3期205-209,共5页上海大学学报（英文版）

基　　金：Project supported by the National Natural Science Foundation of China （Grant No.60502039）, the Shanghai Rising-Star Program （Grant No.06QA14022）, and the Key Project of Shanghai Municipality for Basic Research （Grant No.04JC14037）

摘　　要：In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.In this work, image feature vectors are formed for blocks containing sufficient information, which are selected using a singular-value criterion. When the ratio between the first two SVs axe below a given threshold, the block is considered informative. A total of 12 features including statistics of brightness, color components and texture measures are used to form intermediate vectors. Principal component analysis is then performed to reduce the dimension to 6 to give the final feature vectors. Relevance of the constructed feature vectors is demonstrated by experiments in which k-means clustering is used to group the vectors hence the blocks. Blocks falling into the same group show similar visual appearances.

关 键 词：image feature COLOR TEXTURE content-based image retrieval （CBIR） image hashing 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]