Evolutionary design for image filter using GA

This paper describes evolutionary image filter design for noise reduction using Genetic Algorithm (GA), where the circuit complexity, power and signal delay are optimized. First, the evaluating value about correctness, complexity, power and signal delay are introduced to the fitness function. Then GA autonomously synthesizes a circuit which is simple and has good performance. To verify the effectiveness of our method, an image filter for noise reduction is experimentally synthesized. The resultant image filter by GA and the quality of filtered image are discussed.

[1]  TomasM art ´ inek.  An Evolvable Image Filter: Experimental Evaluation of a Complete Hardware Implementation in FPGA , 2005 .

[2]  Lukás Sekanina,et al.  Evaluation of a New Platform For Image Filter Evolution , 2007, Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007).

[3]  Daniel A. Ashlock,et al.  Evolutionary computation for modeling and optimization , 2005 .

[4]  Tughrul Arslan,et al.  Evolvable Components—From Theory to Hardware Implementations , 2005, Genetic Programming and Evolvable Machines.

[5]  James A. Foster,et al.  Special Purpose Image Convolution with Evolvable Hardware , 2000, EvoWorkshops.

[6]  Lukas Sekanina,et al.  An evolvable hardware system in Xilinx Virtex II Pro FPGA , 2007 .

[7]  Takahiro Watanabe,et al.  A novel Genetic Algorithm with cell crossover for circuit design optimization , 2009, 2009 IEEE International Symposium on Circuits and Systems.

[8]  Xin Yao,et al.  Promises and challenges of evolvable hardware , 1996, IEEE Trans. Syst. Man Cybern. Part C.

[9]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[10]  Lukás Sekanina,et al.  Evolutionary Design of Digital Circuits: Where Are Current Limits? , 2006, First NASA/ESA Conference on Adaptive Hardware and Systems (AHS'06).

[11]  Hitoshi Iba,et al.  Evolving hardware with genetic learning: a first step towards building a Darwin machine , 1993 .

[12]  Kenji Toda,et al.  Real-world applications of analog and digital evolvable hardware , 1999, IEEE Trans. Evol. Comput..

[13]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[14]  Hugo de Garis,et al.  EVOLVABLE HARDWARE Genetic Programming of a Darwin Machine , 1993 .

[15]  Lukás Sekanina,et al.  Image Filter Design with Evolvable Hardware , 2002, EvoWorkshops.