DocumentCode
2968213
Title
Searching similar images — Vector quantization with S-tree
Author
Platos, Jan ; Kromer, Pavel ; Snasel, Vaclav ; Abraham, Ajith
Author_Institution
Dept. of Comput. Sci., VSB-Tech. Univ. of Ostrava, Ostrava, Czech Republic
fYear
2012
fDate
21-23 Nov. 2012
Firstpage
384
Lastpage
388
Abstract
Searching of similar pictures was in the past based mainly on searching of similar picture names. We try to find an effective method how to search pictures by searching of similar information in the picture (histograms, shapes, blocks,). There already are some methods but still not effective enough. In this paper we describe a method where we combine vector quantization (VQ) and fuzzy S-trees. Work contains testing of our approach and you can see results in a final chapter of this paper. The benefit of this work is not the final solution but we put a key-stone for further research and for optimizations. First tests show up the efficiency and usefulness of our approach, which is under laid by executed tests.
Keywords
fuzzy set theory; image retrieval; tree data structures; trees (mathematics); vector quantisation; VQ; fuzzy S-trees; image retrieval; modified data structure; similar image searching; similar information searching; similar picture name searching; vector quantization; Algorithm design and analysis; Clustering algorithms; Image coding; Image color analysis; Testing; Vector quantization; Vectors; fuzzy sets; image similarity; s-tree; vector quantization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Aspects of Social Networks (CASoN), 2012 Fourth International Conference on
Conference_Location
Sao Carlos
Print_ISBN
978-1-4673-4793-8
Type
conf
DOI
10.1109/CASoN.2012.6412433
Filename
6412433
Link To Document