Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/41581
Title: Invariant and perceptually consistent texture mapping for content-based image retrieval
Authors: Long, H.
Tan, C.W. 
Leow, W.K. 
Issue Date: 2001
Source: Long, H.,Tan, C.W.,Leow, W.K. (2001). Invariant and perceptually consistent texture mapping for content-based image retrieval. IEEE International Conference on Image Processing 2 : 117-120. ScholarBank@NUS Repository.
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.
Source Title: IEEE International Conference on Image Processing
URI: http://scholarbank.nus.edu.sg/handle/10635/41581
Appears in Collections:Staff Publications

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