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

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 a better retrieval performance than methods that are not invariant and not perceptually consistent
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
LanguageEnglish
Title of host publicationImage Processing, 2001 : Proceedings. 2001 International Conference on
Volume2
Place of PublicationNew York
PublisherIEEE
Date2001
Pages117-120
ISBN (Print)0780367251
DOIs
StatePublished - 2001
Externally publishedYes
EventInternational Conference on Image Processing 2001 - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001
Conference number: 1
http://conferences.visionbib.com/2001/icip-10-01-call.pdf

Conference

ConferenceInternational Conference on Image Processing 2001
Number1
CountryGreece
CityThessaloniki
Period07/10/200110/10/2001
Internet address

Keywords

    Cite this

    Long, H., Tan, C-W., & Leow, W. K. (2001). Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval. In Image Processing, 2001: Proceedings. 2001 International Conference on (Vol. 2, pp. 117-120). New York: IEEE. DOI: 10.1109/ICIP.2001.958438
    Long, Huizhong ; Tan, Chee-Wee ; Leow, Wee Kheng. / Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval. Image Processing, 2001: Proceedings. 2001 International Conference on. Vol. 2 New York : IEEE, 2001. pp. 117-120
    @inproceedings{347da83b9c5d417080406a75930565d2,
    title = "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 a better retrieval performance than methods that are not invariant and not perceptually consistent",
    keywords = "Content-based retrieval, Image matching, Image texture, Neural nets, Visual databases, Visual perception",
    author = "Huizhong Long and Chee-Wee Tan and Leow, {Wee Kheng}",
    year = "2001",
    doi = "10.1109/ICIP.2001.958438",
    language = "English",
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    }

    Long, H, Tan, C-W & Leow, WK 2001, Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval. in Image Processing, 2001: Proceedings. 2001 International Conference on. vol. 2, IEEE, New York, pp. 117-120, Thessaloniki, Greece, 07/10/2001. DOI: 10.1109/ICIP.2001.958438

    Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval. / Long, Huizhong; Tan, Chee-Wee; Leow, Wee Kheng.

    Image Processing, 2001: Proceedings. 2001 International Conference on. Vol. 2 New York : IEEE, 2001. p. 117-120.

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

    TY - GEN

    T1 - Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval

    AU - Long,Huizhong

    AU - Tan,Chee-Wee

    AU - Leow,Wee Kheng

    PY - 2001

    Y1 - 2001

    N2 - 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

    AB - 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

    KW - Content-based retrieval

    KW - Image matching

    KW - Image texture

    KW - Neural nets

    KW - Visual databases

    KW - Visual perception

    U2 - 10.1109/ICIP.2001.958438

    DO - 10.1109/ICIP.2001.958438

    M3 - Article in proceedings

    SN - 0780367251

    VL - 2

    SP - 117

    EP - 120

    BT - Image Processing, 2001

    PB - IEEE

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    Long H, Tan C-W, Leow WK. Invariant and Perceptually Consistent Texture Mapping for Content-Based Image Retrieval. In Image Processing, 2001: Proceedings. 2001 International Conference on. Vol. 2. New York: IEEE. 2001. p. 117-120. Available from, DOI: 10.1109/ICIP.2001.958438