The surface-shape operator and its application to image retrieval

This paper proposes an operator called the surface-shape sperator for describing image structures. By considering an image function as a surface, the surface-shape operator is established for describing the shape of each pixel compared 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 the usefulness of the proposed approach with the image retrieval application. By comparing the Wold features, the multiresolution simultaneous autoregressive features and the proposed features, the proposed features can provide the best pattern retrieval accuracy.