Invariant and perceptually consistent texture mapping for content-based image retrieval

Abstract

Texture is an important visual feature for content-based image retrieval. An ideal content-based retrieval system should compare images in its database with the query in a manner that is consistent with human's perception of visual similarity. Moreover, texture matching should be invariant to texture scale and orientation because the same texture can appear in the images in varying scales and orientations. In practice, however, texture similarity computed using computational texture features is not necessarily consistent with human's perception. This paper presents a method of mapping texture features into a texture space that is scale and orientation invariant, and at the same time, consistent with human's perception. Test results show that this method achieves better retrieval performance than methods that are not invariant and not perceptually consistent.