A Wavelet-Based Image Indexing, Clustering, and Retrieval Technique Based on Edge Feature

Authors:
Masaaki Kubo;Zaher Aghbari;Kun Seok Oh;Akifumi Makinouchi
Affiliations:
-;-;-;-
Venue:
WAA '01 Proceedings of the Second International Conference on Wavelet Analysis and Its Applications
Year:
2001

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Abstract

This paper proposes a technique for indexing, clustering and retrieving images based on their edge features. In this technique, images are decomposed into several frequency bands using the Haar wavelet transform. From the one-level decomposition sub-bands an edge image is formed. Next, the higher order auto-correlation function is applied on the edge image to extract the edge features. These higher order autocorrelation features are normalized to generate a compact feature vector, which is invariant to shift, image size and gray level. Then, these feature vectors are clustered by a self-organizing map (SOM) based on their edge feature similarity. The performed experiments show the high precision of this technique in clustering and retrieving images in a large image database environment.