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Region-Based Image Retrieval using Radial Basis Function Network

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3 Author(s)
Kui Wu ; Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ. ; Kim-Hui Yap ; Chau, L.-P.

This paper presents a new framework that integrates relevance feedback into region-based image retrieval (RBIR) systems based on radial basis function network (RBFN). A modified unsupervised subtractive clustering algorithm is proposed for RBFN center selection according to the characteristics of region-based image representation. A new kernel function of RBFN is introduced for image similarity comparison under region-based representation. The underlying network parameters (weight and width) are then optimized using a supervised gradient-descent training strategy. Experimental results using a database of 10,000 images demonstrate the effectiveness of the proposed hybrid learning approach

Published in:

Multimedia and Expo, 2006 IEEE International Conference on

Date of Conference:

9-12 July 2006