Automatic similarity learning using SOTM for CBIR of the WT/VQ coded images

The unsupervised learning network is explored to incorpo rate self learning capability into image retrieval systems More speci cally we propose the adoption of a Self Or ganizing Tree Map SOTM to implement a self learning methodology that allows minimization of the role of users in an e ort to automate interactive retrieval This automatic learning mode is applied to interactive retrieval strategies such as the radial basis function method and the relevance feedback method The proposed method has been applied to retrieve the images compressed by wavelet transform and vector quantization coders Retrieval performances are compared with conventional retrieval systems employ ing both non interactive and user controlled interactive re trieval using the MIT texture database The results ob tained are compared favorably with preceding methods