Abstract
The long term goal of the work described in this paper is the development of a bio-inspired system, employing evolvable hardware, that adapts according to the needs of the environment in which it is deployed. The application described here is the design of a novel and highly parallel image processing tool to detect edges within a wide range of conventional grey-scale images. We discuss the simulation of such a system based on a genetic programming paradigm, using a simple binary logic tree to implement the genetic string coding. The results acquired from the simulation are compared with those obtained from the application of a conventional Sobel edge detector, and although rudimentary, show the great potential of such bio-inspired systems.
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References
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison-Wesley, Reading (1993)
Haralick, R.M.: Digital step edges from zero crossing of second directional deriva- tives. IEEE Trans. Pattern Anal. Machine Intell. PAMI-6, 58–68 (1984)
Heath, M., Sarkar, S., Sanocki, T., Bowyer, K.W.: A robust visual method for assessing the realtive performance of edge-detection algorithms. IEEE Transactions on Pattern and Machine Intelligence 19(12), 1338–1359 (1996)
Holland, J.H.: Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor (1975)
Hollingworth, G.S., Smith, S.L., Tyrrell, A.M.: Design of highly parallel edge detection nodes using evolutionary techniques. In: Proceedings of 7th Euromicro Workshop on Parallel and Distributed Processing. IEEE Press, Los Alamitos (1999)
Iba, H., Iwata, M., Higuchi, T.: Gate-level Evolvable Hardware: Empirical study and application, pp. 259–279. Springer, Heidelberg (1997)
Xilinx inc.: Xc6200 field programmable gate array data book (1995), http://www.xilinx.com/partinfo/6200.pdf
Iwata, M., Kajitani, I., Yamada, H., Iba, H., Higuchi, T.: A pattern recognition system using evolvable hardware. In: International Conference on Evolutionary Computation: The 4th Conference on Parallel Problem Solving from Nature, pp. 761–770. Springer, Heidelberg (1996)
Koza, J.R.: Genetic Programming. MIT Press, Cambridge (1992)
Murakawa, M., Yoshizawa, S., Higuchi, T.: Adaptive equalisation of digital communication channels using evolvable hardware. In: Higuchi, T., Iwata, M., Weixin, L., et al. (eds.) ICES 1996. LNCS, vol. 1259, pp. 379–389. Springer, Heidelberg (1997)
Murakawa, M., Yoshizawa, S., Kajitani, I., Furuya, T., Iwata, M., Higuchi, T.: Hardware evolution at functional level. In: International conference on Evolutionary Computation: The 4th Conference on Parallel Problem Solving from Nature, pp. 62–71 (1996)
Ortega, C., Tyrrell, A.M.: Biologically inspired real-time reconfiguration tech- nique for processor arrays. In: Proceedings of 5th IFAC Workshop on Algorithms and Architectures for Real-Time Control (1998)
Ortega, C., Tyrrell, A.M.: Design of a basic cell to construct embryonic arrays (1998)
Sipper, M.: Designing evolware by cellular programming. In: Higuchi, T., Iwata, M., Weixin, L. (eds.) ICES 1996. LNCS, vol. 1259, pp. 81–95. Springer, Heidelberg (1997)
Sobel, I.E.: Camera models and machine perception, phd thesis (1970)
Thompson, A.: Evolving Electronic Robot Controllers that exploit hardware resources, pp. 640–656. Springer, Heidelberg (1995)
Thompson, A.: Evolutionary techniques for fault tolerance. In: UKACC International Conference on Control, pp. 693–698 (1996)
Thompson, A.: An evolved circuit, intrinsic in silicon, entwined with physics. In: Higuchi, T., Iwata, M., Weixin, L. (eds.) ICES 1996. LNCS, vol. 1259. Springer, Heidelberg (1997)
Thompson, A.: Silicon evolution. In: Koza, J.R., et al. (eds.) Proceedings of Genetic Programming 1996 (GP 1996), pp. 444–452. MIT Press, Cambridge (1996)
Vernon, D.: Machine Vision: Automated Visual Inspection and Robot Vision. Prentice Hall, Englewood Cliffs (1991)
Von Neumann, J.: Theory of Self Reproducing Automata. University of Illinois Press, Urbana (1966)
Yao, X., Higuchi, T.: Promises and challenges of evolvable hardware. In: International Conference on Evolvable Systems: From Biology to Hardware. Springer, Heidelberg (1996)
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Hollingworth, G., Tyrrell, A., Smith, S. (1999). Simulation of Evolvable Hardware to Solve Low Level Image Processing Tasks. In: Poli, R., Voigt, HM., Cagnoni, S., Corne, D., Smith, G.D., Fogarty, T.C. (eds) Evolutionary Image Analysis, Signal Processing and Telecommunications. EvoWorkshops 1999. Lecture Notes in Computer Science, vol 1596. Springer, Berlin, Heidelberg. https://doi.org/10.1007/10704703_4
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DOI: https://doi.org/10.1007/10704703_4
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