Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval

Huizhong Long, Chee-Wee Tan, Wee Kheng Leow

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


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 a better retrieval performance than methods that are not invariant and not perceptually consistent
Original languageEnglish
Title of host publicationProceedings of the 2001 International Conference on Image Processing. ICIP 2001. Vol. 2
Number of pages4
Place of PublicationLos Alamitos, CA
Publication date2001
ISBN (Print)0780367251
Publication statusPublished - 2001
Externally publishedYes
EventInternational Conference on Image Processing 2001 - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001
Conference number: 1


ConferenceInternational Conference on Image Processing 2001
Internet address

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