Lexicographic Image Hash Based on Space and Frequency Features  

作　　者：ZHAO Yan ZHAO Qian TONG Ming-lei 赵琰;赵倩;仝明磊(School of Electronic and Information Engineering,Shanghai University of Electric Power)

机构地区：School of Electronic and Information Engineering, Shanghai University of Electric Power, Shanghai 200090 , China

出　　处：《Journal of Donghua University(English Edition)》2016年第6期899-902,共4页东华大学学报（英文版）

基　　金：Natural Science Foundations of Shanghai,China(Nos.15ZR1418500,15ZR1418400);the Training Program of Shanghai University of Electric Power for Academic Backbone Teachers,China

摘　　要：A lexicographic image hash method based on space and frequency features was proposed. At first, the image database was constructed, and then color and texture features were extracted from the image blocks including information for every image in the database, which formed feature vectors. The feature vectors were clustered to form dictionary. In hash generation, the image was preproc^ssed and divided into blocks firstly. Then color and texture features vectors were extracted from the blocks. These feature vectors were used to search the dictionary, and the nearest word in dictionary for each block was used to form the space features. At the same time. frequency feature was extracted from each block. The space and frequency features were connected to form the intermediate hash. Lastly, the final hash sequence was obtained by pseudo-randomly permuting the intermediate hash. Experiments show that the method has a very low probability of collision and a good perception of robustness. Compared with other methods, this method has a low collision rate.A lexicographic image hash method based on space and frequency features was proposed.At first,the image database was constructed,and then color and texture features were extracted from the image blocks including information for every image in the database,which formed feature vectors.The feature vectors were clustered to form dictionary.In hash generation,the image was preprocessed and divided into blocks firstly.Then color and texture features vectors were extracted from the blocks.These feature vectors were used to search the dictionary,and the nearest word in dictionary for each block was used to form the space features.At the same time,frequency feature was extracted from each block.The space and frequency features were connected to form the intermediate hash.Lastly,the final hash sequence was obtained by pseudo-randomly permuting the intermediate hash.Experiments show that the method has a very low probability of collision and a good perception of robustness.Compared with other methods,this method has a low collision rate.

关 键 词：image hash LEXICOGRAPHIC discrete cosine transform(DCT) image authentication 

分 类 号：TP391.6[自动化与计算机技术—计算机应用技术]