SELF-ORGANIZING IMAGE RETRIEVAL WITH MPEG-7 DESCRIPTORS

Development of content-based image retrieval techniques has suffered from the lack of standardized ways for describing visual image content. Luckily, MPEG-7 is now emerging as both a framework for content description and a collection of specic, agreed-upon content descriptors. We have developed a neural, self-organizing technique for content-based image re- trieval in our image retrieval system named PicSOM. In this paper, we apply the visual content descriptors provided by MPEG-7 in the PicSOM system and compare our indexing technique with a reference system. The results of our experiments show that the MPEG-7-dened con- tent descriptors can be used as such in PicSOM even though Euclidean distance calculation, inherently used in the PicSOM system, is not optimal for all of them.

[1]  Erkki Oja,et al.  Self-Organizing Maps of Web Link Information , 2001, WSOM.

[2]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[3]  Hujun Yin,et al.  Advances in Self-Organising Maps, WSOM 2001, Lincoln, UK, 13-15 June, 2011 , 2001, WSOM.

[4]  E. Oja,et al.  COMPARISON OF TECHNIQUES FOR CONTENT-BASED IMAGE RETRIEVAL , 2001 .

[5]  Shih-Fu Chang,et al.  Overview of the MPEG-7 standard , 2001, IEEE Trans. Circuits Syst. Video Technol..

[6]  Erkki Oja,et al.  Self-Organising Maps as a Relevance Feedback Technique in Content-Based Image Retrieval , 2001, Pattern Analysis & Applications.

[7]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[8]  Erkki Oja,et al.  PicSOM - content-based image retrieval with self-organizing maps , 2000, Pattern Recognit. Lett..

[9]  Pasi Koikkalainen,et al.  Self-organizing hierarchical feature maps , 1990, 1990 IJCNN International Joint Conference on Neural Networks.