Abstract
In this work a system based on genetic algorithms is presented that generates valid initializations for deformable models methods. Following a systematics similar to that used by other authors, a model of the shape we are looking for (cows in lateral position) is constructed using PDM, and later the search within the image is made based on instances of that model, and using genetic algorithms techniques. Since we have color images, several objective functions are suggested that take advantage of this information, which are tested later over a database of 309 animal images taken directly in the field.
This is a preview of subscription content, log in via an institution to check access.
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
Cootes, T. F., Hill, A., Taylor, C. J., Haslam, J.: The Use of Active Shape Models For Locating Structures in Medical Images. Image and Vision Computing, vol 12, no 6, pp 335–366. July 1994.
Cootes, T. F., Taylor, C. J., Cooper D. H., Graham, J.: Active Shape models-Their Training and Application. Computer Vision and Image Understanding, vol 61, no 1, pp 38–59. Jan. 1995.
Felkel, P., Mrázek, P., Sýkora, L., Zára, J., Jezek, B.: On Segmentation for Medical Data Visualization. Proc. of EWVSC’96, pp 189–198. April 1996.
Goldberg, D. E.: Genetic Algorithms in Search Optimization and Machine Learning. Addison-Wesley, 1989
González, H. M., López, F. J., García, C. J., Macías, M., Acevedo, M. I.: Application of ANN Techniques to Automated Identification of Bovine Livestock. Proc. Of IWANN’99, pp 422–431. June 1999.
Hill, A., Cootes, T. F., Taylor, C. J., Lindley, K.: Medical Image Interpretation: A Generic Approach using Deformable Templates. Journal of Medical Informatics, vol 19, no 1, pp 47–59. Jan. 1994.
Hill, A., Taylor, C. J.: Model-Based Image Interpretation Using Genetic Algorithms. Image and Vision Computing, vol. 10, no 5, pp 295–300. June 1992.
Hug, J., Brechbühler, C., Székely, G.: Model-based Initialisation for Segmentation. Proc. of ECCV 2000, pp 290–306. June 2000.
Jain, A. K.: Fundamentals of Digital Image Processing. Prentice Hall, 1989
Lanitis, A., Hill, A., Cootes, T. F., Taylor, C. J.: Locating Facial Features Using Genetic Algorithms. Procs. of ICDSP’95, pp.520–525. 1995.
López, S., Goyache, F., Quevedo, J. R. et al.: Un Sistema Inteligente para Calificar Morfológicamente a Bovinos de la Raza Asturiana de los Valles, Revista Iberoamericana de Inteligencia Artificial, no 10, pp 5–17. 2000.
Sánchez-Belda, A.: Razas Bovinas Espa~nolas. Manual Técnico, Ministerio de Agricultura, Pesca y Alimentación. España, 1984.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
González Velasco, H.M., García Orellana, C.J., Macías Macías, M., Acevedo Sotoca, M.I. (2001). GA Techniques Applied to Contour Search in Images of Bovine Livestock. In: Mira, J., Prieto, A. (eds) Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence. IWANN 2001. Lecture Notes in Computer Science, vol 2084. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45720-8_57
Download citation
DOI: https://doi.org/10.1007/3-540-45720-8_57
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42235-8
Online ISBN: 978-3-540-45720-6
eBook Packages: Springer Book Archive