DocumentCode :
3309401
Title :
Fractal Image Compression Using Genetic Algorithm
Author :
Bobde, Sarika Sanjay ; Kulkarni, M.V. ; Kulkarni, P.V.
Author_Institution :
Dept. of Comput. Eng., Univ. of Pune, Pune, India
fYear :
2010
fDate :
20-21 June 2010
Firstpage :
241
Lastpage :
243
Abstract :
This paper gives the improved method of generating a binary image IFS using Genetic Algorithm. To find the maps of IFSs that can encode black and white (BW) images, the Genetic Algorithm uses a variable-length genotype representation, i.e., each IFS is represented as a list of maps, and a map is represented as a set of real parameters. Special genetic operators that maintain and control the feasibility of the individuals in the population are adopted. A fitness function is defined that measures the similarity between the attractor and the image that penalizes a large number of maps and high contractivity factors.
Keywords :
Biological cells; Evolutionary computation; Extraterrestrial measurements; Fractals; Genetic algorithms; Genetic engineering; Image coding; Image generation; Image segmentation; Wavelet domain; Fractal Image Compression; Genetic Algorithm; Iterated Function System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computer Engineering (ACE), 2010 International Conference on
Conference_Location :
Bangalore, Karnataka, India
Print_ISBN :
978-1-4244-7154-6
Type :
conf
DOI :
10.1109/ACE.2010.9
Filename :
5532835
Link To Document :
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