Abstract
Image processing is usually done by chaining a series of well known image processing operators. Using evolutionary methods this process may be automated. In this paper we address the problem of evolving task specific image processing operators. In general, the quality of the operator depends on the task and the current environment. Using genetic programming we evolved an interest operator which is used to calculate sparse optical flow. To evolve the interest operator we define a series of criteria which need to be optimized. The different criteria are combined into an overall fitness function. Finally, we present experimental results on the evolution of the interest operator.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Andre, D.: Automatically defined features: The simultaneous evolution of 2-dimensional feature detectors and an algorithm for using them. In: Kinnear Jr., K.E. (ed.) Advances in Genetic Programming, pp. 477–494. The MIT Press, Cambridge (1994)
Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D.: Genetic Programming - An Introduction: On The Automatic Evolution of Computer Programs and Its Applications. Morgan Kaufmann Publishers, San Francisco (1998)
Bhattacharjya, A.K., Roysam, B.: Joint solution of low, intermediate, and highlevel vision tasks by evolutionary optimization: Application to computer vision at low SNR. IEEE Transactions on Neural Networks 5(1), 83–95 (1994)
Brooks, R.R., Iyengar, S.S., Chen, J.: Automatic correlation and calibration of noisy sensor readings using elite genetic algorithms. Artificial Intelligence 84, 339–354 (1996)
Daida, J.M., Hommes, J.D., Bersano-Begey, T.F., Ross, S.J., Vesecky, J.F.: Algorithm discovery using the genetic programming paradigm: Extracting low contrast curvilinear features from sar images of arctic ice. In: Angeline, P.J., Kinnear Jr., K.E. (eds.) Advances in Genetic Programming, vol. II, pp. 417–442. MIT Press, Cambridge (1996)
Ebner, M.: On the evolution of edge detectors for robot vision using genetic programming. In: Groβ, H.-M. (ed.) Workshop SOAVE 1997 - Selbstorganisation von Adaptivem Verhalten, VDI Reihe 8 Nr. 663, pp. 127–134. VDI Verlag (1997)
Ebner, M.: On the evolution of interest operators using genetic programming. In: Poli, R., Langdon, W.B., Schoenauer, M., Fogarty, T., Banzhaf, W. (eds.) Late Breaking Papers at EuroGP 1998: the First European Workshop on Genetic Programming, Paris, France, pp. 6–10. The University of Birmingham, UK (1998)
Fonseca, C.M., Fleming, P.J.: An overview of evolutionary algorithms in multiobjective optimization. Evolutionary Computation 3(1), 1–16 (1995)
Harris, C., Buxton, B.: Evolving edge detectors with genetic programming. In: Koza, J.R., Goldberg, D.E., Fogel, D.B., Riolo, R.L. (eds.) Genetic Programming 1996, Proceedings of the First Annual Conference, pp. 309–314. The MIT Press, Cambridge (1996)
Jain, R., Kasturi, R., Schunck, B.G.: Machine Vision. McGraw-Hill, New York (1995)
Johnson, M.P., Maes, P., Darrell, T.: Evolving visual routines. In: Brooks, R.A., Maes, P. (eds.) Artificial Life IV, Proceedings of the Fourth International Workshop on the Synthesis and Simulation of Living Systems, pp. 198–209. The MIT Press, Cambridge (1994)
Kalinke, T., von Seelen, W.: Entropie als Maβ des lokalen Informationsgehalts in Bildern zur Realisierung einer Aufmerksamkeitssteuerung. In: Jähne, B., Geiβler, P., Hauβecker, H., Hering, F. (eds.) Mustererkennung 1996, 18. DAGM Symposium, pp. 627–634. Springer, Heidelberg (1996)
Katz, A.J., Thrift, P.R.: Generating image filters for target recognition by genetic learning. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(9), 906–910 (1994)
Koza, J.R.: Genetic Programming, On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge (1992)
Koza, J.R.: Genetic Programming II, Automatic Discovery of Reusable Programs. The MIT Press, Cambridge (1994)
Lampinen, J., Oja, E.: Distortion tolerant pattern recognition based on selforganizing feature extraction. IEEE Transactions on Neural Networks 6(3), 539–547 (1995)
Lew, M.S., Huang, T.S., Wong, K.: Learning and feature selection in stereo matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(9), 869–881 (1994)
Lohmann, R.: Selforganization by evolution strategy in visual systems. In: Voigt, H.-M., Mühlenbein, H., Schwefel, H.-P. (eds.) Evolution and Optimization 1989, pp. 61–68. Akademie-Verlag, Berlin (1990)
Mallot, H.A.: Sehen und die Verarbeitung visueller Information, Eine Einführung. Vieweg, Braunschweig (1998)
Moravec, H.P.: Towards automatic visual obstacle avoidance. In: Proc. of the 5th International Joint Conference on Artificial Intelligence, Vision-1, p. 584 (1977)
Poli, R.: Genetic programming for image analysis. In: Koza, J.R., Goldberg, D.E., Fogel, D.B., Riolo, R.L. (eds.) Genetic Programming 1996, Proceedings of the First Annual Conference, pp. 363–368. The MIT Press, Cambridge (1996)
Poli, R., Cagnoni, S.: Genetic programming with user-driven selection: Experiments on the evolution of algorithms for image enhancement. In: Koza, J.R., Deb, K., Dorigo, M., Fogel, D.B., Fogel, D.B., Garzon, M., Iba, H., Riolo, R.L. (eds.) Genetic Programming 1997, Proceedings of the Second Annual Conference, pp. 269–277. Morgan Kaufmann Publishers, San Francisco (1996)
Pope, A.R., Lowe, D.G.: Vista: A software environment for computer vision research. In: Proceedings of the 1994 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 768–772. IEEE, Los Alamitos (1994)
Reisfeld, D., Wolfson, H., Yeshurun, Y.: Detection of interest points using symmetry. In: Proceedings of the International Conference on Computer Vision, Osaka, Japan, pp. 62–65. IEEE, Los Alamitos (1990)
Rizki, M.M., Tamburino, L.A., Zmuda, M.A.: Evolving multi-resolution feature-detectors. In: Fogel, D.B., Atmar, W. (eds.) Proceedings of the Second American Conference on Evolutionary Programming. pp. 108–118. Evolutionary Programming Society (1993)
Roth, G., Levine, M.D.: Geometric primitive extraction using a genetic algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 16(9), 901–905 (1994)
Shah, M.A., Jain, R.: Detecting time-varying corners. Computer Vision, Graphics, and Image Processing 28, 345–355 (1984)
Shi, J., Tomasi, C.: Good features to track. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)
Smith, S.: A new class of corner finder. Proceedings of the 3rd British Machine Vision Conference 1992, pp. 139–148 (1992)
Tackett, W.A.: Genetic programming for feature discovery and image discrimination. In: Forrest, S. (ed.) Proceedings of the Fifth International Conerence on Genetic Algorithms, pp. 303–309. Morgan Kaufmann, San Francisco (1993)
Tovée, M.J.: An introduction to the visual system. Cambridge University Press, Cambridge (1996)
Ullman, S.: Visual routines. In: Fischler, M.A., Firschein, O. (eds.) Readings in Computer Vision: Issues, Problems, Principles, and Paradigms, Los Altos, California, pp. 298–328. Morgan Kaufmann Publishers, San Francisco (1987)
Winkeler, J.F., Manjunath, B.S.: Genetic programming for object detection. In: Koza, J.R., Deb, K., Dorigo, M., Fogel, D.B., Fogel, D.B., Garzon, M., Iba, H., Riolo, R.L. (eds.) Genetic Programming 1997, Proceedings of the Second Annual Conference, pp. 330–335. Morgan Kaufmann Publishers, San Francisco (1997)
Xie, M.: Automatic feature matching in uncalibrated stereo vision through the use of color. Robotics and Autonomous Systems 21, 355–364 (1997)
Zabrodsky, H., Peleg, S., Avnir, D.: Symmertry as a continuous feature. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(12), 1154–1165 (1995)
Zheng, Q., Chellappa, R.: Automatic feature point extraction and tracking in image sequences for arbitrary camera motion. International Journal of Computer Vision 15, 31–76 (1995)
Zongker, D., Punch, B.: lil-gp 1.01 User’s Manual (support and enhancements Bill Rand). Michigan State University (March 1996)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ebner, M., Zell, A. (1999). Evolving a Task Specific Image Operator. 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_6
Download citation
DOI: https://doi.org/10.1007/10704703_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65837-5
Online ISBN: 978-3-540-48917-7
eBook Packages: Springer Book Archive