Color- and texture-based image segmentation using EM and its application to content-based image retrieval

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Color- and texture-based image segmentation using EM and its application to content-based image retrieval. / Belongie, S; Carson, C; Greenspan, H; Malik, J.

SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION. NAROSA PUBLISHING HOUSE, 1998. p. 675-682.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Belongie, S, Carson, C, Greenspan, H & Malik, J 1998, Color- and texture-based image segmentation using EM and its application to content-based image retrieval. in SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION. NAROSA PUBLISHING HOUSE, pp. 675-682, 6th International Conference on Computer Vision, BOMBAY, India, 04/01/1998. https://doi.org/10.1109/ICCV.1998.710790

APA

Belongie, S., Carson, C., Greenspan, H., & Malik, J. (1998). Color- and texture-based image segmentation using EM and its application to content-based image retrieval. In SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION (pp. 675-682). NAROSA PUBLISHING HOUSE. https://doi.org/10.1109/ICCV.1998.710790

Vancouver

Belongie S, Carson C, Greenspan H, Malik J. Color- and texture-based image segmentation using EM and its application to content-based image retrieval. In SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION. NAROSA PUBLISHING HOUSE. 1998. p. 675-682 https://doi.org/10.1109/ICCV.1998.710790

Author

Belongie, S ; Carson, C ; Greenspan, H ; Malik, J. / Color- and texture-based image segmentation using EM and its application to content-based image retrieval. SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION. NAROSA PUBLISHING HOUSE, 1998. pp. 675-682

Bibtex

@inproceedings{a6cd92b0049a4a46abe51f75ab27bd66,
title = "Color- and texture-based image segmentation using EM and its application to content-based image retrieval",
abstract = "Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present a new image representation which provides a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. This so-called {"}blobworld{"} representation is based on segmentation using the Expectation-Maximization algorithm on combined color and texture features, The texture features we use for the segmentation arise from a new approach to texture description and scale selection.We describe a system that uses the blobworld representation to retrieve images.;In important and unique aspect of the system is that, in the concert of similarity-based querying, the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer The user this view into the workings of the system; consequently, the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.",
author = "S Belongie and C Carson and H Greenspan and J Malik",
year = "1998",
doi = "10.1109/ICCV.1998.710790",
language = "English",
isbn = "81-7319-221-9",
pages = "675--682",
booktitle = "SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION",
publisher = "NAROSA PUBLISHING HOUSE",
note = "6th International Conference on Computer Vision ; Conference date: 04-01-1998 Through 07-01-1998",

}

RIS

TY - GEN

T1 - Color- and texture-based image segmentation using EM and its application to content-based image retrieval

AU - Belongie, S

AU - Carson, C

AU - Greenspan, H

AU - Malik, J

PY - 1998

Y1 - 1998

N2 - Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present a new image representation which provides a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. This so-called "blobworld" representation is based on segmentation using the Expectation-Maximization algorithm on combined color and texture features, The texture features we use for the segmentation arise from a new approach to texture description and scale selection.We describe a system that uses the blobworld representation to retrieve images.;In important and unique aspect of the system is that, in the concert of similarity-based querying, the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer The user this view into the workings of the system; consequently, the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.

AB - Retrieving images from large and varied collections using image content as a key is a challenging and important problem. In this paper we present a new image representation which provides a transformation from the raw pixel data to a small set of image regions which are coherent in color and texture space. This so-called "blobworld" representation is based on segmentation using the Expectation-Maximization algorithm on combined color and texture features, The texture features we use for the segmentation arise from a new approach to texture description and scale selection.We describe a system that uses the blobworld representation to retrieve images.;In important and unique aspect of the system is that, in the concert of similarity-based querying, the user is allowed to view the internal representation of the submitted image and the query results. Similar systems do not offer The user this view into the workings of the system; consequently, the outcome of many queries on these systems can be quite inexplicable, despite the availability of knobs for adjusting the similarity metric.

U2 - 10.1109/ICCV.1998.710790

DO - 10.1109/ICCV.1998.710790

M3 - Article in proceedings

SN - 81-7319-221-9

SP - 675

EP - 682

BT - SIXTH INTERNATIONAL CONFERENCE ON COMPUTER VISION

PB - NAROSA PUBLISHING HOUSE

T2 - 6th International Conference on Computer Vision

Y2 - 4 January 1998 through 7 January 1998

ER -

ID: 302162296