Content-Based Image Retrieval Technique Using Wavelet-Based Shift and Brightness Invariant Edge Feature
Masaaki Kubo, Zaher Al Aghbari, Akifumi Makinouchi, Kun Seok Oh · International Journal of Wavelets Multiresolution and Information Processing · 2003
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 autocorrelation 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.