EFFICIENT ROTATION INVARIANT TEXTURE FEATURES FOR CONTENT-BASED IMAGE RETRIEVAL

摘要

An efficient approach to the extraction of rotation invariant texture features is presented. Histograms of intensity gradient directions are compiled. Rotation invariant features are extracted by taking the Fourier expansion of the histogram. The method is applied to image database annotation and content based retrieval. With a database of over 400 randomly rotated images all textures are correctly identified on the return of two classifications. On presentation of a texture to the image retrieval system nine out of ten images returned from the search are of the same texture as the query image. Its simplicity and accuracy render the method highly suited to applications such as content-based image retrieval. The method requires no human intervention. Extensive experimental results are included to demonstrate the performance of the method in texture classification and content-based retrieval.