DocumentCode :
3493421
Title :
Partitioned fractal image compression for binary images using genetic algorithms
Author :
Aggarwal, Arpit ; Kunal, R.
Author_Institution :
Indian Inst. of Information Technol., Allahabad, India
fYear :
2005
fDate :
19-22 March 2005
Firstpage :
734
Lastpage :
737
Abstract :
The paper presents a novel approach for pre-processing of binary images, which helps in subsequent application of the genetic algorithm in a parallel manner and reduces the computational time, while at the same time improves the quality of the regenerated image and makes the evolutionary approach more practical to employ for fractal image compression. Pre-processing involves division of image into disconnected regions, identification of the largest solid rectangle and final partitioning about the rectangle. The performance of the proposed partitioned technique is tested on a binary image and the experimental results are reported.
Keywords :
data compression; genetic algorithms; image coding; binary image preprocessing; computational time reduction; genetic algorithms; largest solid rectangle; partitioned fractal image compression; Concurrent computing; Decoding; Discrete wavelet transforms; Fractals; Genetic algorithms; Image coding; Information technology; Partitioning algorithms; Solids; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2005. Proceedings. 2005 IEEE
Print_ISBN :
0-7803-8812-7
Type :
conf
DOI :
10.1109/ICNSC.2005.1461281
Filename :
1461281
Link To Document :
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