NDLI: Implementation of image segmentation and reconstruction using genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Aravind, I. Chandra, C. Guruprasad, M. Dev, P.S. Samuel, R.D.S.
Copyright Year	2002
Description	Author affiliation: Dept. of Electron. & Commun., Sri Jayachamarajendra Coll. of Eng., Mysore, India (Aravind, I.; Chandra, C.; Guruprasad, M.; Dev, P.S.; Samuel, R.D.S.)
Abstract	This paper describes an approach of using genetic algorithms (GAs) for image segmentation. The approach proposes to solve the problem based on the idea of using genetic programming to discover effective problem-specific filters capable of highly and selectively emphasizing some characteristics of the image. Genetic algorithms work on the principle of simulation of the evolution of individual structures via processes such as selection, mutation, and reproduction. Implementation of image segmentation using GAs involves identifying a suitable binary coding strategy, defining a fitness evaluation function, designing a population' (set of chromosomes), defining genetically inspired operators such as crossover and mutation to evolve new population and deciding the termination of the evolutionary search for the optimal solution. Segmentation is a non polynomial type of problem. This paper describes the use of genetic algorithms in the randomized search of solution to the segmentation problem, with the initial population built using the state space techniques and then evolved using genetic operators and the fitness function. Accuracy of the results is found to vary with the fitness function. The result is got in the binary form due the coding strategy adapted. A mask is then implemented to extract and reconstruct the segmented image from the original image.
Sponsorship	IEEE Ind. Electron. Soc. Thai Robotics Soc
Starting Page	970
Ending Page	975
File Size	309742
Page Count	6
File Format	PDF
ISBN	0780376579
DOI	10.1109/ICIT.2002.1189301
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-12-11
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image reconstruction Genetic algorithms Genetic mutations Genetic programming Filters Image coding Biological cells Polynomials State-space methods
Content Type	Text
Resource Type	Article

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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
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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
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