Texture-based image indexing in the process of lossless data compression

Abstract

The authors describe a new approach for content-based image indexing and retrieval by extracting texture features from the process of image compression via JPEG-LS. Since the compression technique adopted incorporates local edge detection to formulate predictive values for pixels being encoded, the texture features extracted by the proposed algorithms are also capable of describing image content in terms of edges and shapes of local objects without adding any significant complexity to the original JPEG-LS. While lossless data compression helps in saving storage space automatically for image databases, the extensive experiments also show that this type of feature extraction produces better retrieval results in comparison with existing similar indexing techniques which are carried out without data compression.