A Novel Genetic Programming Algorithm for Designing Morphological Image Analysis Method

In this paper, we propose an applicable genetic programming approach to solve the problems of binary image analysis and gray scale image enhancement. Given a section of original image and the corresponding goal image, the proposed algorithm evolves for generations and produces a mathematic morphological operation sequence, and the result performed by which is close to the goal. When the operation sequence is applied to the whole image, the objective of image analysis is achieved. In this sequence, only basic morphological operations-- erosion and dilation, and logical operations are used. The well-defined chromosome structure leads brings about more complex morphological operations can be composed in a short sequence. Because of a reasonable evolution strategy, the evolution effectiveness of this algorithm is guaranteed. Tested by the binary image features analysis, this algorithm runs faster and is more accurate and intelligible than previous works. In addition, when this algorithm is applied to infrared finger vein gray scale images to enhance the region of interest, more accurate features are extracted and the accuracy of discrimination is promoted.

[1]  David G. Stork,et al.  Pattern Classification , 1973 .

[2]  Stephanie Forrest,et al.  Proceedings of the 5th International Conference on Genetic Algorithms , 1993 .

[3]  Sung-Bae Cho,et al.  A Novel Evolutionary Approach to Image Enhancement Filter Design: Method and Applications , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[4]  Walter Alden Tackett,et al.  Genetic Programming for Feature Discovery and Image Discrimination , 1993, ICGA.

[5]  Agostinho C. Rosa,et al.  Gray-scale image enhancement as an automatic process driven by evolution , 2004, IEEE Trans. Syst. Man Cybern. Part B.

[6]  Pierre Soille,et al.  Morphological Image Analysis: Principles and Applications , 2003 .

[7]  Riccardo Poli,et al.  Morphological algorithm design for binary images using genetic programming , 2006, Genetic Programming and Evolvable Machines.

[8]  Riccardo Poli,et al.  On Two Approaches to Image Processing Algorithm Design for Binary Images Using GP , 2003, EvoWorkshops.

[9]  David G. Stork,et al.  Pattern Classification (2nd ed.) , 1999 .

[10]  Lakhmi C. Jain,et al.  Computational Intelligence: A Compendium , 2008, Computational Intelligence: A Compendium.

[11]  John R. Koza,et al.  Genetic programming - on the programming of computers by means of natural selection , 1993, Complex adaptive systems.

[12]  Hiromitsu Yamada,et al.  Automatic acquisition of hierarchical mathematical morphology procedures by genetic algorithms , 1999, Image Vis. Comput..

[13]  Rolf Drechsler,et al.  Applications of Evolutionary Computing, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Proceedings , 2008, EvoWorkshops.

[14]  R. Poli.  Genetic programming for image analysis , 1996 .

[15]  Anil K. Jain,et al.  A modified Hausdorff distance for object matching , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[16]  Stephen Marshall,et al.  The use of genetic algorithms in morphological filter design , 1996, Signal Process. Image Commun..

[17]  Daniel P. Huttenlocher,et al.  Comparing Images Using the Hausdorff Distance , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  Riccardo Poli,et al.  Genetic Programming: An Introduction and Tutorial, with a Survey of Techniques and Applications , 2008, Computational Intelligence: A Compendium.

[19]  Jason M. Daida,et al.  Algorithm discovery using the genetic programming paradigm: extracting low-contrast curvilinear features from SAR images of arctic ice , 1996 .

[20]  Lucia Ballerini,et al.  Genetic Optimization of Morphological Filters with Applications in Breast Cancer Detection , 2004, EvoWorkshops.

[21]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[22]  Peter J. Angeline,et al.  Algorithm Discovery using the Genetic Programming Paradigm: Extracting Low-Contrast Curvilinear Features from SAR Images of Arctic Ice , 1996 .