Title :
A Novel Image Semantic Block Clustering Method based on Artificial Visual Cortical Responding Model
Author :
XU, Zhiping ; Zhang, Shiyong ; Ma, Shengxiang
Author_Institution :
Dept. of Comput. & Inf. Technol., Fudan Univ., Shanghai
fDate :
March 1 2007-April 5 2007
Abstract :
This paper proposed a novel visual information process model named artificial visual cortical responding model (AVCRM) to obtain the invariable time sequence response feature from the sub-image block in the image. By compressing the time sequence feature and selecting the important points in the sequence, we compared the compressed version of sequences with each other to generate the distance matrix. According to distance matrix, we clustered the sub-images into the initially manually assigned concept categories to attain the semantic distribution map of the image. This mechanism was proved to be effective through the experiments and made a good semantic foundation of the future content based image retrieval research work
Keywords :
data compression; feature extraction; image coding; pattern clustering; artificial visual cortical responding model; distance matrix; image retrieval; image semantic block clustering; invariable time sequence response feature; semantic distribution map; subimage clustering; time sequence feature compression; visual information process model; Clustering methods; Content based retrieval; Image retrieval; Information technology; Neurons; Optical feedback; Optical filters; Optical interconnections; Optical sensors; Visual system;
Conference_Titel :
Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0705-2
DOI :
10.1109/CIDM.2007.368877