DocumentCode
2724556
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
fYear
2007
fDate
March 1 2007-April 5 2007
Firstpage
228
Lastpage
233
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
Conference_Location
Honolulu, HI
Print_ISBN
1-4244-0705-2
Type
conf
DOI
10.1109/CIDM.2007.368877
Filename
4221301
Link To Document