NDLI: A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping

Content Provider	Springer Nature Link
Author	Han, XiaoHong Xiong, Xiaoyan Duan, Fu
Copyright Year	2015
Abstract	This paper proposes a novel image segmentation method based on BP neural network, which is optimized by an enhanced Gravitational Search Algorithm (GSA). GSA is a novel heuristic optimization algorithm based on the law of gravity and mass interactions. It has been proven that the GSA has good ability to search for the global optimum, but it suffers from the premature convergence due to the rapid reduction of diversity. This work introduces a cat chaotic mapping into the steps of population initialization and iterative stage of the original GSA, which forms a new algorithm called CCMGSA. Then the CCMGSA is employed to optimize BP neural networks, which forms a combination method called CCMGSA-BP and we use it for image segmentation. To verify the efficiency of this method, the visual and performance experiments are done. The visual results using our proposed method are compared with those using other segmentation methods including an improved k-means clustering algorithm (I-K-means), a hybrid region merging method (H-Region-merging), and manual segmentation. The comparison results show that the proposed method can get good segmentation results on grayscale images with specific characteristics. And we compare the performance of our proposed method with those of IGSA-BP, CLPSO-BP and RGA-BP for image segmentation. The results indicate that the CCMGSA-BP shows better performance in terms of the convergence rate and avoidance of local minima.
Starting Page	855
Ending Page	873
Page Count	19
File Format	PDF
ISSN	0924669X
Journal	Applied Intelligence
Volume Number	43
Issue Number	4
e-ISSN	15737497
Language	English
Publisher	Springer US
Publisher Date	2015-07-02
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image segmentation Gravitational search algorithm Cat chaotic mapping Neural network Optimization algorithm Back-Propagation algorithm Artificial Intelligence (incl. Robotics) Mechanical Engineering Manufacturing, Machines, Tools
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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

Generation of suprasegmental information for speech using a recurrent neural network and binary gravitational search algorithm for feature selection

An optimized classification algorithm by BP neural network based on PLS and HCA

A Novel Self-Organizing Neural Network for Motion Segmentation

An enhanced hybrid method for time series prediction using linear and neural network models

A Hierarchical Neural Network Document Classifier with Linguistic Feature Selection

Dynamic partition search algorithm for global numerical optimization

Document segmentation using textural features summarization and feedforward neural network

A Neural Network Parallel Algorithm for Meeting Schedule Problems

Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm

A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping

Similar Documents

Generation of suprasegmental information for speech using a recurrent neural network and binary gravitational search algorithm for feature selection

An optimized classification algorithm by BP neural network based on PLS and HCA

A Novel Self-Organizing Neural Network for Motion Segmentation

An enhanced hybrid method for time series prediction using linear and neural network models

A Hierarchical Neural Network Document Classifier with Linguistic Feature Selection

Dynamic partition search algorithm for global numerical optimization

Document segmentation using textural features summarization and feedforward neural network

A Neural Network Parallel Algorithm for Meeting Schedule Problems

Control and synchronization of chaotic systems by an improved biogeography-based optimization algorithm

A new method for image segmentation based on BP neural network and gravitational search algorithm enhanced by cat chaotic mapping