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