Finding boundaries in natural images: A new method using point descriptors and area completion

Research output: Contribution to journal › Conference article › Research › peer-review

Standard

Finding boundaries in natural images : A new method using point descriptors and area completion. / Belongie, Serge; Malik, Jitendra.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1998, p. 751-766.

Research output: Contribution to journal › Conference article › Research › peer-review

Harvard

Belongie, S & Malik, J 1998, 'Finding boundaries in natural images: A new method using point descriptors and area completion', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 751-766. https://doi.org/10.1007/BFb0055702

APA

Belongie, S., & Malik, J. (1998). Finding boundaries in natural images: A new method using point descriptors and area completion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 751-766. https://doi.org/10.1007/BFb0055702

Vancouver

Belongie S, Malik J. Finding boundaries in natural images: A new method using point descriptors and area completion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1998;751-766. https://doi.org/10.1007/BFb0055702

Author

Belongie, Serge ; Malik, Jitendra. / Finding boundaries in natural images : A new method using point descriptors and area completion. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 1998 ; pp. 751-766.

Bibtex

@inproceedings{fb633605d82d4f569ea12822f828e9b3,
title = "Finding boundaries in natural images: A new method using point descriptors and area completion",
abstract = "We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their responses to a set of filters. However, this approach brings with it many open questions, including how to combine texture and intensity information into a common descriptor and how to deal with the fact that filter responses inside textured regions are generally spatially inhomogeneous. Our goal in this paper is to introduce two new ideas which address these open questions and to demonstrate the application of these ideas to the segmentation of natural images. The first idea consists of a novel means of describing points in natural images and an associated distance function for comparing these descriptors. This distance function is aided in textured regions by the use of the second idea, a new process introduced here which we have termed area completion. Experimental segmentation results which incorporate our proposed approach into the Normalized Cut framework of Shi and Malik are provided for a variety of natural images.",
author = "Serge Belongie and Jitendra Malik",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 1998.; 5th European Conference on Computer Vision, ECCV 1998 ; Conference date: 02-06-1998 Through 06-06-1998",
year = "1998",
doi = "10.1007/BFb0055702",
language = "English",
pages = "751--766",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Verlag",

}

RIS

TY - GEN

T1 - Finding boundaries in natural images

T2 - 5th European Conference on Computer Vision, ECCV 1998

AU - Belongie, Serge

AU - Malik, Jitendra

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 1998.

PY - 1998

Y1 - 1998

N2 - We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their responses to a set of filters. However, this approach brings with it many open questions, including how to combine texture and intensity information into a common descriptor and how to deal with the fact that filter responses inside textured regions are generally spatially inhomogeneous. Our goal in this paper is to introduce two new ideas which address these open questions and to demonstrate the application of these ideas to the segmentation of natural images. The first idea consists of a novel means of describing points in natural images and an associated distance function for comparing these descriptors. This distance function is aided in textured regions by the use of the second idea, a new process introduced here which we have termed area completion. Experimental segmentation results which incorporate our proposed approach into the Normalized Cut framework of Shi and Malik are provided for a variety of natural images.

AB - We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their responses to a set of filters. However, this approach brings with it many open questions, including how to combine texture and intensity information into a common descriptor and how to deal with the fact that filter responses inside textured regions are generally spatially inhomogeneous. Our goal in this paper is to introduce two new ideas which address these open questions and to demonstrate the application of these ideas to the segmentation of natural images. The first idea consists of a novel means of describing points in natural images and an associated distance function for comparing these descriptors. This distance function is aided in textured regions by the use of the second idea, a new process introduced here which we have termed area completion. Experimental segmentation results which incorporate our proposed approach into the Normalized Cut framework of Shi and Malik are provided for a variety of natural images.

UR - http://www.scopus.com/inward/record.url?scp=78149347366&partnerID=8YFLogxK

U2 - 10.1007/BFb0055702

DO - 10.1007/BFb0055702

M3 - Conference article

AN - SCOPUS:78149347366

SP - 751

EP - 766

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

Y2 - 2 June 1998 through 6 June 1998

ER -

ID: 302060581