DocumentCode :
794778
Title :
PicSOM-self-organizing image retrieval with MPEG-7 content descriptors
Author :
Laaksonen, Jorma ; Koskela, Markus ; Oja, Erkki
Author_Institution :
Lab. of Comput. & Inf. Sci., Helsinki Univ. of Technol., Espoo, Finland
Volume :
13
Issue :
4
fYear :
2002
fDate :
7/1/2002 12:00:00 AM
Firstpage :
841
Lastpage :
853
Abstract :
Development of content-based image retrieval (CBIR) techniques has suffered from the lack of standardized ways for describing visual image content. Luckily, the MPEG-7 international standard is now emerging as both a general framework for content description and a collection of specific agreed-upon content descriptors. We have developed a neural, self-organizing technique for CBIR. Our system is named PicSOM and it is based on pictorial examples and relevance feedback (RF). The name stems from "picture" and the self-organizing map (SOM). The PicSOM system is implemented by using tree structured SOMs. In this paper, we apply the visual content descriptors provided by MPEG-7 in the PicSOM system and compare our own image indexing technique with a reference system based on vector quantization (VQ). The results of our experiments show that the MPEG-7-defined content descriptors can be used as such in the PicSOM system even though Euclidean distance calculation, inherently used in the PicSOM system, is not optimal for all of them. Also, the results indicate that the PicSOM technique is a bit slower than the reference system in starting to find relevant images. However, when the strong RF mechanism of PicSOM begins to function, its retrieval precision exceeds that of the reference system.
Keywords :
content-based retrieval; image retrieval; self-organising feature maps; CBIR; Euclidean distance calculation; MPEG-7 content descriptors; PicSOM; RF; VQ; content-based image retrieval; image indexing technique; international standard; neural self-organizing technique; pictorial examples; relevance feedback; self-organizing image retrieval; vector quantization; visual image content; Associate members; Computer vision; Content based retrieval; Humans; Image retrieval; Indexing; MPEG 7 Standard; Neurofeedback; Radio frequency; Vector quantization;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2002.1021885
Filename :
1021885
Link To Document :
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