Surface-shape operator and its application to image retrieval

This paper proposes an operator called the Surface-Shape operator for describing image structures. By considering an image function as a surface, the Surface-Shape operator is established for describing shape of each pixel comparing with its neighbourhood. In this paper, the Surface-Shape operator is used as a pre-processing for describing the multiscale topographic structures of images in scale-space representation. Then, image features are extracted from the transformed images instead of the original ones. The Surface-Shape operator has invariant properties under linear and monotonic gray tone transformations, and is insensitive to additive noises modelled by linear functions so it has robustness with brightness variations and shading effects. Finally, we show usefulness of the proposed approach with the image retrieval application. By comparing among the Wold features, the Multiresolution Simultaneous Autoregressive features and the proposed features, the proposed features can provide the best pattern retrieval accuracy.