A NICHE BASED GENETIC ALGORITHM FOR IMAGE REGISTRATION

Giuseppe Pascale, Luigi Troiano

Abstract

Image registration aims to find the unknown set of transformations able to reduce two or more images to a common reference frame. Image registration can be regarded as an optimization problem, where the goal is to maximize a measure of image similarity. The measure of similarity on the overall image can be computationally expensive, leading to measure the similarity of smaller subimages. However, the reduction of subimage size results into a higher multi-modality for the optimizing function. Recent investigations have shown that genetic algorithms can address this problem. However, the simple scheme of genetic algorithms can still fall in local optima. In this paper, we explore the application of niche-oriented genetic algorithms, showing their strengths in providing a more effective image registration algorithm.

References

  1. Brown, L. G. (1992). A survey of image registration techniques. ACM Computing Surveys, 24:325-376.
  2. De Jong, K. A. (1975). An analysis of the behavior of a class of genetic adaptive systems. PhD thesis.
  3. Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison Wesley.
  4. Goldberg, D. E. and Richardson, J. (1987). Genetic algorithms with sharing for multimodal function optimization. In Proc. of the II Int. Conf. on Genetic Algorithms on Genetic Algorithms and Their Application, pages 41-49, Mahwah, NJ, USA. Lawrence Erlbaum Associates, Inc.
  5. Mahfoud, S. W. (1992). Crowding and preselection revisited. Parallel Problem Solving from Nature, 2:27-37.
  6. Mahfoud, S. W. (1995). Niching methods for genetic algorithms. Technical Report 1894, Department of Computer Science, University of Illinois at UrbanaChampaign, Urbana, Illinois.
  7. Townshend, J. R. G., Justice, C. O., Gurney, C., and McManus, J. (1992). The impact of misregistration on change detection. IEEE Transaction on Geoscience and Remote Sensing, 30(5):1054-1060.
  8. Zitová, B. and Flusser, J. (2003). Image registration methods: a survey. Image Vision Computation, 21(11):977-1000.
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Paper Citation


in Harvard Style

Pascale G. and Troiano L. (2007). A NICHE BASED GENETIC ALGORITHM FOR IMAGE REGISTRATION . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-972-8865-89-4, pages 342-347. DOI: 10.5220/0002382003420347


in Bibtex Style

@conference{iceis07,
author={Giuseppe Pascale and Luigi Troiano},
title={A NICHE BASED GENETIC ALGORITHM FOR IMAGE REGISTRATION},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2007},
pages={342-347},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002382003420347},
isbn={978-972-8865-89-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - A NICHE BASED GENETIC ALGORITHM FOR IMAGE REGISTRATION
SN - 978-972-8865-89-4
AU - Pascale G.
AU - Troiano L.
PY - 2007
SP - 342
EP - 347
DO - 10.5220/0002382003420347