Image thresholding based on Ali-Silvey distance measures

Liane C. Ramac; Pramod K. Varshney

doi:10.1016/S0031-3203(96)00149-5

Image thresholding based on Ali-Silvey distance measures

Liane C. Ramac, Pramod K. Varshney

Department of Electrical Engineering & Computer Science

Research output: Contribution to journal › Article › peer-review

31 Scopus citations

Abstract

A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number of members of this class are selected and used for implementation in image thresholding algorithms. Performance is evaluated by applying these algorithms to several images and comparing them to a few histogram based thresholding methods,

Original language	English (US)
Pages (from-to)	1161-1174
Number of pages	14
Journal	Pattern Recognition
Volume	30
Issue number	7
DOIs	https://doi.org/10.1016/S0031-3203(96)00149-5
State	Published - Jul 1997

Keywords

Ali-silvey distance measures
Co-occurrence matrix
Image processing
Relative entropy
Segmentation
Thresholding

ASJC Scopus subject areas

Software
Signal Processing
Computer Vision and Pattern Recognition
Artificial Intelligence

Access to Document

10.1016/S0031-3203(96)00149-5

Cite this

@article{3e59d7a77eec4b58a3047d817a52b63a,

title = "Image thresholding based on Ali-Silvey distance measures",

abstract = "A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number of members of this class are selected and used for implementation in image thresholding algorithms. Performance is evaluated by applying these algorithms to several images and comparing them to a few histogram based thresholding methods,",

keywords = "Ali-silvey distance measures, Co-occurrence matrix, Image processing, Relative entropy, Segmentation, Thresholding",

author = "Ramac, {Liane C.} and Varshney, {Pramod K.}",

note = "Funding Information: 1Effort sponsored by Rome Laboratory, Air Force Material Command, USAF, under grant number F30602-95-1-0027. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Rome Laboratory or the U.S. Government.",

year = "1997",

month = jul,

doi = "10.1016/S0031-3203(96)00149-5",

language = "English (US)",

volume = "30",

pages = "1161--1174",

journal = "Pattern Recognition",

issn = "0031-3203",

publisher = "Elsevier",

number = "7",

}

TY - JOUR

T1 - Image thresholding based on Ali-Silvey distance measures

AU - Ramac, Liane C.

AU - Varshney, Pramod K.

N1 - Funding Information: 1Effort sponsored by Rome Laboratory, Air Force Material Command, USAF, under grant number F30602-95-1-0027. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright annotation thereon. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of Rome Laboratory or the U.S. Government.

PY - 1997/7

Y1 - 1997/7

N2 - A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number of members of this class are selected and used for implementation in image thresholding algorithms. Performance is evaluated by applying these algorithms to several images and comparing them to a few histogram based thresholding methods,

AB - A relative entropy based approach to image thresholding was proposed recently. It was demonstrated that this method was successful for image thresholding. Relative entropy is a member of the class of Ali-Silvey distance measures. In this paper we generalize the relative entropy based approach and present image thresholding algorithms based on the class of Ali-Silvey distance measures. A number of members of this class are selected and used for implementation in image thresholding algorithms. Performance is evaluated by applying these algorithms to several images and comparing them to a few histogram based thresholding methods,

KW - Ali-silvey distance measures

KW - Co-occurrence matrix

KW - Image processing

KW - Relative entropy

KW - Segmentation

KW - Thresholding

UR - http://www.scopus.com/inward/record.url?scp=0031188373&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0031188373&partnerID=8YFLogxK

U2 - 10.1016/S0031-3203(96)00149-5

DO - 10.1016/S0031-3203(96)00149-5

M3 - Article

AN - SCOPUS:0031188373

SN - 0031-3203

VL - 30

SP - 1161

EP - 1174

JO - Pattern Recognition

JF - Pattern Recognition

IS - 7

ER -

Image thresholding based on Ali-Silvey distance measures

Abstract

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this