Abstract
The characterization techniques of forms can be usually classified grosso modo between global and local techniques. The complexity of the images to be analized imposes strong limitations to the freedom of choice about the model of description to be used. So the global techniques are used in enviroments where the objects to be classified are simple in nature and do not overlap. On the other side, the employement of local techniques is required as the starting point for the description of more complex scenes, linking this local characterization to some process of structural inference. When some measures, obtained from the raw data, are used in the description we find a set of techniques which can be grouped under the term of transformed representations. They all have in common the ability to reduce the amount of data to be analized without degrading substantially the semantics of the image.
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References
Anderberg, M.R., 1973, Cluster Analysis for Applications, Academic Press, New York.
Cabrera J., Falcón A., Hernández F.M., Méndez J., 1991, A Systematic Method for Exploring Contour Segments Descriptions, Proc. EUROCAST’91, Springer Lecture Notes in Computer Science, (To be published).
Falcón A., Méndez J., 1984, Localization y Orientación de Piezas en Sistemas visuales de Reconocimiento, Actas II Simposium Nacional IFAC de Automática en la industria, pp.209–212, Zaragoza.
Hernández F.M., 1987, Reconocimiento de Formas Tridimensionales mediante Caracterización Global de Vistas, Doctoral Thesis, Univ. Politécnica de Canarias. Las Palmas de Gran Canaria.
Jain N., Indrayan A., Goel L.R., 1986, Monte Carlo Comparison of six Hierarchical Clustering Methods on Random Data, Pattern Recog., 19:95.
Méndez J., 1983, Contribuciones a la Teoría de Caracterización de Formas para el Reconocimiento, Doctoral Thesis, Univ. Politécnica de Las Palmas, Las Palmas de Gran Canaria.
Méndez J., Falcón A., 1984, On the Orthogonal Expansion of Images for Low Level Recognition. Fourier-Bessel Representation, Proc. First Conf. Art. Int. Applic, pp. 167–169, IEEE Press, Denver, Col.
Shlien S., 1990, Multiple Binary Decision Tree Classifiers, Pattern Recog., 23:757.
Wang Q.R., Suen C.Y., 1987, Large Tree Classifier with Heuristic Search and Global Training, IEEE Trans. on Patttern Anal. Mach. Intell., 9:91.
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Cabrera, J., Falcón, A., Hernández, F.M., Méndez, J. (1991). An Experimental Approach to The Description of Contour Segments using the Fourier-Bessel Transform. In: Jackson, M.C., Mansell, G.J., Flood, R.L., Blackham, R.B., Probert, S.V.E. (eds) Systems Thinking in Europe. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-3748-9_30
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DOI: https://doi.org/10.1007/978-1-4615-3748-9_30
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