NDLI: An Efficient Image Segmentation Method Based on Fuzzy Particle Swarm Optimization and Markov Random Field Model

Content Provider	IEEE Xplore Digital Library
Author	Guoying Liu Aimin Wang Yuanqing Zhao
Copyright Year	2011
Abstract	In order to overcome the poor anti-noise performance of traditional fuzzy C-Means (FCM) algorithm in image segmentation, a novel improved FCM algorithm was proposed in this paper based on Particle Swarm Optimization (PSO) algorithm and Markov Random Field (MRF) model, which can make full use of the global searching ability of PSO and the spatial information integrating ability of MRF for image segmentation. In this algorithm, the image segmentation is converted to a PSO optimization problem, in which the fitness function is set up to containing the spatial information based on the spectral value and the neighboring pixels modeled by MRFs. And segmentation results can be iteratively obtained during the PSO iterations according to the newly designed membership function of FCM in which the spatial information is integrated. The experiments herein reported in this paper illustrate the better performance of this algorithm than the traditional FCM algorithm and the PSO algorithm for image segmentation.
Starting Page	1
Ending Page	4
File Size	198695
Page Count	4
File Format	PDF
ISBN	9781424462506
ISSN	21619654
e-ISBN	9781424462520
DOI	10.1109/wicom.2011.6040554
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Computers Image segmentation Noise Clustering algorithms Particle swarm optimization Markov random fields
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

An efficient automatic hierarchical image segmentation algorithm based on Modal Analysis and Mutational Agglomeration

A new image segmentation algorithm based the fusion of Markov random field and fuzzy c-means clustering

Image Segmentation Based on Modified Particle Swarm Optimization and Fuzzy C-Means Clustering

A niching particle swarm segmentation of infrared images

Image Segmentation Using Fast Fuzzy C Means Based on Particle Swarm Optimization

A novel cerebrovascular segmentation approach based on Markov random field and particle swarm optimization algorithm

A hybridized clustering approach using particle swarm optimization for image segmentation

Medical Image Segmentation Using Particle Swarm Optimization

The proposal of a fuzzy clustering algorithm based on particle swarm

An Efficient Image Segmentation Method Based on Fuzzy Particle Swarm Optimization and Markov Random Field Model

Similar Documents

An efficient automatic hierarchical image segmentation algorithm based on Modal Analysis and Mutational Agglomeration

A new image segmentation algorithm based the fusion of Markov random field and fuzzy c-means clustering

Image Segmentation Based on Modified Particle Swarm Optimization and Fuzzy C-Means Clustering

A niching particle swarm segmentation of infrared images

Image Segmentation Using Fast Fuzzy C Means Based on Particle Swarm Optimization

A novel cerebrovascular segmentation approach based on Markov random field and particle swarm optimization algorithm

A hybridized clustering approach using particle swarm optimization for image segmentation

Medical Image Segmentation Using Particle Swarm Optimization

The proposal of a fuzzy clustering algorithm based on particle swarm

An Efficient Image Segmentation Method Based on Fuzzy Particle Swarm Optimization and Markov Random Field Model