Image retrieval via isotropic and anisotropic mappings

摘要

This paper presents an approach for content-based image retrieval via isotropic and anisotropic mappings. Isotropic mappings are defined as mappings invariant to the action of the planar Euclidean group on the image space—invariant to the translation, rotation and reflection of image data, and hence, invariant to orientation and position. Anisotropic mappings, on the other hand, are defined as those mappings that are correspondingly variant. Structure extraction (via a perceptual grouping process) and color histogram are shown to be representations of isotropic mappings. Texture analysis using a channel energy model comprised of even-symmetric Gabor filters is considered to be a representation of anisotropic mapping. An integration framework for these mappings is developed. Results of retrieval of outdoor images by query and by classification using a nearest neighbor classifier are presented.