Evolutionary Image Analysis, Signal Processing and Telecommunications

In this work we examine the applicability of an evolutionary strategy to the problem of fitting constrained second-order surfaces to both synthetic and acquired 3D data. In particular we concentrate on the Genocop III algorithm proposed by Michalewicz [8] for the optimization of constrained functions. This is a novel application of this algorithm which has demonstrably good results when applied using parametric models. Example times for convergence are given which compare the approach to standard techniques.

[1]  Chris Loader Local Search Algorithms for 2D Geometric Object Recognition , 1995 .

[2]  Erkki Oja,et al.  Randomized hough transform (rht) : Basic mech-anisms, algorithms, and computational complexities , 1993 .

[3]  Justinian Rosca,et al.  Generality versus size in genetic programming , 1996 .

[4]  Marco Tomassini,et al.  A phylogenetic, ontogenetic, and epigenetic view of bio-inspired hardware systems , 1997, IEEE Trans. Evol. Comput..

[5]  L. Steels Perceptually grounded meaning creation , 1996 .

[6]  Luc Steels,et al.  The Construction and Acquisition of Visual Categories , 1997, EWLR.

[7]  Riccardo Poli,et al.  Evolution of Graph-Like Programs with Parallel Distributed Genetic Programming , 1997, ICGA.

[8]  Luc Steels,et al.  The synthetic modeling of language origins , 1997 .

[9]  Trevor Darrell,et al.  Evolving Visual Routines , 1994, Artificial Life.

[10]  Karen B. Sarachik Limitations of Geometric Hashing in the Presence of Gaussian Noise , 1992 .

[11]  Vidroha Debroy,et al.  Genetic Programming , 1998, Lecture Notes in Computer Science.

[12]  A. Dempster,et al.  Use of minimum-adder multiplier blocks in FIR digital filters , 1995 .

[13]  J. Shynk Adaptive IIR filtering , 1989, IEEE ASSP Magazine.

[14]  Julian Francis Miller,et al.  Aspects of Digital Evolution: Geometry and Learning , 1998, ICES.

[15]  John G. Proakis,et al.  Digital Communications , 1983 .

[16]  Tetsuya Higuchi,et al.  Adaptive Equalization of Digital Communication Channels Using Evolvable Hardware , 1996, ICES.

[17]  Azriel Rosenfeld,et al.  Using probabilistic domain knowledge to reduce the expected computational cost of template matching , 1990, Comput. Vis. Graph. Image Process..

[18]  David Bull,et al.  Design of low complexity FIR filters using genetic algorithms and directed graphs , 1997 .

[19]  Martin D. Levine,et al.  Geometric Primitive Extraction Using a Genetic Algorithm , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Ken Sharman,et al.  Some Applications of Genetic Programming in Digital Signal Processing , 1996 .

[21]  William Rucklidge,et al.  Locating objects using the Hausdorff distance , 1995, Proceedings of IEEE International Conference on Computer Vision.

[22]  R. Weale Vision. A Computational Investigation Into the Human Representation and Processing of Visual Information. David Marr , 1983 .

[23]  Riccardo Poli,et al.  Fitness Causes Bloat: Mutation , 1997, EuroGP.

[24]  Emmanuel Ifeachor,et al.  Automating IIR filter design by genetic algorithm , 1995 .

[25]  David B. Fogel,et al.  Gaining Insight into Evolutionary Programming Through Landscape Visualization: An Investigation into IIR Filtering , 1997, Evolutionary Programming.

[26]  Arthur R. Pope Model-Based Object Recognition - A Survey of Recent Research , 1994 .

[27]  Juyang Weng,et al.  Genetic algorithms for object recognition in a complex scene , 1995, Proceedings., International Conference on Image Processing.

[28]  Leonid P. Jaroslavskij Digital picture processing , 1985 .

[29]  Paul Vogt,et al.  How should a robot discriminate between objects? a comparison between two methods , 1998 .

[30]  Jerzy W. Bala,et al.  Using Learning to Facilitate the Evolution of Features for Recognizing Visual Concepts , 1996, Evolutionary Computation.

[31]  G. G. Cameron,et al.  Genetic algorithm implementation of stack filter design for image restoration , 1996 .

[32]  T. Soule,et al.  Code Size and Depth Flows in Genetic Programming , 1997 .