Texture features for browsing and retrieval of image data
Department of Electrical and Computer Engineering
University of California, Santa Barbara, CA 93106
Image content based retrieval is emerging as an important research area with application to digital libraries and multimedia databases. The focus or this paper is on the image processing aspects and in paricular using texture information for browsing and retrieval of large image data. We propose the use of Gabor wavelet features for texture analysis and provide a comprehensive experimental evaluation. Comparisons with other multiresolution texture features using the Brodatz texture database indicate that the Gabor features provide the best pattern retrieval accuracy. An application to browsing large air photos is illustrated.