Texture based image indexing and retrieval

The Content Based Image Retrieval (CBIR) has been an active research area. Given a collection of images, it is to retrieve the images based on a query image, which is specified by content. The present method uses a new technique based on wavelet transformations by which a feature vector of size ten, characterizing texture feature of the images is constructed. Our method derives feature vector(10 signatures) for each image characterizing the texture feature of sub image from only three iterations of wavelet transforms. A clustering method ROCK is modified and used to cluster the group of images based on feature vectors of sub images of database by considering the minimum Euclidean distance. This modified ROCK is used to minimize searching process. Our experiments are conducted on a variety of garment images and successful matching results are obtained.