A HVS-driven image segmentation framework using a local segmentation performance measure

Renbin Peng; Pramod K. Varshney

doi:10.1109/wnyipw.2010.5649767

A HVS-driven image segmentation framework using a local segmentation performance measure

Renbin Peng, Pramod K. Varshney

Department of Electrical Engineering & Computer Science

Research output: Chapter in Book/Entry/Poem › Conference contribution

Abstract

This paper presents a novel framework for image segmentation. In this framework, image segmentation is considered to be a detection problem, and a "soft" segmentation objective function, in terms of the detection performance measure in local regions, is employed to guide the segmentation procedure. The human visual system information is also incorporated into the segmentation procedure to improve the efficiency of the framework by introducing a contrast sensitivity function-weighting operation in the wavelet domain. Encouraging experimental results are obtained when the algorithm is applied to real-world image data.

Original language	English (US)
Title of host publication	2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings
Publisher	IEEE Computer Society
Pages	18-21
Number of pages	4
ISBN (Print)	9781424493005
DOIs	https://doi.org/10.1109/wnyipw.2010.5649767
State	Published - 2010

Publication series

Name	2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings

Keywords

Human visual system
Image segmentation
Markov random fields

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Computer Vision and Pattern Recognition

Access to Document

10.1109/wnyipw.2010.5649767

Cite this

Peng, R., & Varshney, P. K. (2010). A HVS-driven image segmentation framework using a local segmentation performance measure. In 2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings (pp. 18-21). [5649767] (2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings). IEEE Computer Society. https://doi.org/10.1109/wnyipw.2010.5649767

A HVS-driven image segmentation framework using a local segmentation performance measure. / Peng, Renbin; Varshney, Pramod K.
2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings. IEEE Computer Society, 2010. p. 18-21 5649767 (2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings).

Research output: Chapter in Book/Entry/Poem › Conference contribution

@inproceedings{ae1a5d60625146038d33e863ecea6da2,

title = "A HVS-driven image segmentation framework using a local segmentation performance measure",

abstract = "This paper presents a novel framework for image segmentation. In this framework, image segmentation is considered to be a detection problem, and a {"}soft{"} segmentation objective function, in terms of the detection performance measure in local regions, is employed to guide the segmentation procedure. The human visual system information is also incorporated into the segmentation procedure to improve the efficiency of the framework by introducing a contrast sensitivity function-weighting operation in the wavelet domain. Encouraging experimental results are obtained when the algorithm is applied to real-world image data.",

keywords = "Human visual system, Image segmentation, Markov random fields",

author = "Renbin Peng and Varshney, {Pramod K.}",

year = "2010",

doi = "10.1109/wnyipw.2010.5649767",

language = "English (US)",

isbn = "9781424493005",

series = "2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings",

publisher = "IEEE Computer Society",

pages = "18--21",

booktitle = "2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings",

address = "United States",

}

TY - GEN

T1 - A HVS-driven image segmentation framework using a local segmentation performance measure

AU - Peng, Renbin

AU - Varshney, Pramod K.

PY - 2010

Y1 - 2010

N2 - This paper presents a novel framework for image segmentation. In this framework, image segmentation is considered to be a detection problem, and a "soft" segmentation objective function, in terms of the detection performance measure in local regions, is employed to guide the segmentation procedure. The human visual system information is also incorporated into the segmentation procedure to improve the efficiency of the framework by introducing a contrast sensitivity function-weighting operation in the wavelet domain. Encouraging experimental results are obtained when the algorithm is applied to real-world image data.

AB - This paper presents a novel framework for image segmentation. In this framework, image segmentation is considered to be a detection problem, and a "soft" segmentation objective function, in terms of the detection performance measure in local regions, is employed to guide the segmentation procedure. The human visual system information is also incorporated into the segmentation procedure to improve the efficiency of the framework by introducing a contrast sensitivity function-weighting operation in the wavelet domain. Encouraging experimental results are obtained when the algorithm is applied to real-world image data.

KW - Human visual system

KW - Image segmentation

KW - Markov random fields

UR - http://www.scopus.com/inward/record.url?scp=78650892699&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650892699&partnerID=8YFLogxK

U2 - 10.1109/wnyipw.2010.5649767

DO - 10.1109/wnyipw.2010.5649767

M3 - Conference contribution

AN - SCOPUS:78650892699

SN - 9781424493005

T3 - 2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings

SP - 18

EP - 21

BT - 2010 Western New York Image Processing Workshop, WNYIPW 2010 - Proceedings

PB - IEEE Computer Society

ER -

A HVS-driven image segmentation framework using a local segmentation performance measure

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this