An Efficient Genetic Encoding Scheme for Multiplierless Color Space Converter Design

Abstract:

Color space conversion has become a very important role in image and video processing systems. To speed up some processing processes, many communication and multimedia video compression schemes use luminance-chrominance type color spaces, such as YCbCr or YUV, making a mechanism for converting between different formats necessary. Therefore, techniques which efficiently implement this conversion are desired. For the recent years, a new field of research called Evolvable Hardware (EHW) has emerged which combines aspects of evolutionary computation with hardware design and synthesis. It is a new scheme inspired by natural evolution, for automatic design of hardware systems. This paper presents a novel evolutionary approach for efficient implementation of a RGB to YCbCr color space converter suitable for Field Programmable Gate Array (FPGAs) and VLSI. In the proposed method, we use the genetic algorithm to automatically evolve the multiplierless architecture of the color space converter. The architecture employs only a few shift and addition operations to replace the complex multiplications. The experimental results represent that the performance of implemented architecture is good at RGB to YCbCr color space converting, and it also has the advantages of high-speed, low-complexity, and low-area.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 3015-3019
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.3015
• Online since: January 2013
• Authors: Ching Yi Chen, Ching Han Chen, Chih Hao Ma, Po Yi Wu
• Keywords: Color Space Conversion, Evolvable Hardware, Genetic Algorithm (GA)

References

[1] H. de Garis, Evolvable Hardware : Genetic Programming of a Darwin Machine, in Proc. of the International conf. on Artificial Neural Nets and Genetic Algorithms, (1993) Innsbruck, Austria.

DOI: 10.1007/978-3-7091-7533-0_64

[2] J. R. Koza, F. H. Bennett III, D. Andre, M. A. Keane, F. Dunlap, Automated Synthesis of Analog Electrical Circuits by Means of Genetic Programming, IEEE Trans. Evol. Comput. 1(2), (1997) 109-128.

DOI: 10.1109/4235.687879

[3] A. Thompson, An evolved circuit, intrinsic in silicon, entwined with physics, in Proc. 1st Int. Conf. on Evolvable Systems, October 7-8 (1997), Tsukuba, Japan.

[4] A. Thompson, On The automatic Design of Robust Electronics Through Artificial Evolution, in Proc. 2nd Int. Conf. on Evolvable Systems, September (1998), Lausanne, Switzerland.

[5] M. Sipper, D. Mange, E. Sanchez, Commun. ACM 42(4), (1999) 50-56.

[6] X. Yao, T. Higuchi, Promises and Challenges of Evolvable Hardware, IEEE Trans. Syst., Man, Cyber. 29(1), (1999) 87-97.

DOI: 10.1109/5326.740672

[7] J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, University of Michigan Press, Ann Arbor, MI, USA, (1975).

[8] S.N. Sivanandam and S.N. Deepa, Introduction to Genetic Algorithms, Springer, New York, (2008).