Selective gray and texture information for image segmentation

DOI

10.2991/icaicte-15.2015.95How to use a DOI?

Keywords

active contour model; Kullback-Leibler distance; Split-Bregman method

Abstract

In this paper, an active contour model is proposed for image segmentation, combining original image and feature image information with adaptive weight. The feature image is a texture descriptor which intrinsically defines the geometry of textures using semi-local image information. The Kullback-Leibler distance is used to design the energy of active contour model, in which the weight coefficient for original image and feature image is decided by the ratio of their distributions entropy. The energy minimization is achieved with Split-Bregman method. The results show that proposed method can achieve automatic segmentation of natural image with minimal parameter compared to related approaches.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Sun Kaiqiong
AU  - Wan Zhiqin
PY  - 2015/08
DA  - 2015/08
TI  - Selective gray and texture information for image segmentation
BT  - Proceedings of the 2015 3d International Conference on Advanced Information and Communication Technology for Education
PB  - Atlantis Press
SP  - 409
EP  - 411
SN  - 2352-538X
UR  - https://doi.org/10.2991/icaicte-15.2015.95
DO  - 10.2991/icaicte-15.2015.95
ID  - Kaiqiong2015/08
ER  -