Image Retrieval by Texture Analysis Based On Angular Spectrum and Gabor Function

The effectiveness of content based retrieval in large image databases, such as video databases where milions of image are stored for each film, depends on the visual features utilized for automatically indexing image data. This paper presents a comparative study of two of the most relevant automatic indexing techniques. The image features compared are extracted by angular spectrum computation and by Gabor function. The image reference set, necessary for performances comparison, is obtained by including in a database of 7154 natural images, frames extracted from video shots. Frames extracted from a shot are different but have the same semantic content. One of these frames is utilized as an example in a query; the indexing effectiveness is assessed from the frames retrieved. Key-Words: image retrieval, texture analysis, angular spectrum, Gabor function.

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