Abstract
A connectionist method for segmenting digital images in grey level is defined. This method relies on the topology preserving property of Kohonen's self-organizing feature maps. This method is adaptive in the sense that the most present on the image an interval of grey values is, the most accurate the segmentation in this range is. Segmentation of various pictures illustrates the method.
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References
T. Kohonen, “Self-organization and associative memory”, Springer-Verlag Berlin, 1984.
T. Kohonen, “The self-organizing feature map”, proceedings of the I.E.E.E., vol. 78, n∘ 9, September 1990.
N.M. Nasrabadi, Y. Feng, “Vector quantization of images based upon the Kohonen self-organizing feature map”, I.E.E.E. Int. Conf. on Neural Networks, pp. 101–108, San Diego California, 1988.
E. le Bail, A. Mitchie, “Quantification vectorielle par le réseau neuronal de Kohonen”, Traitement du Signal, vol. 6, n∘ 6, 1989.
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© 1993 Springer-Verlag Berlin Heidelberg
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Natowicz, R., Sokol, R. (1993). Self-organizing feature maps for image segmentation. In: Mira, J., Cabestany, J., Prieto, A. (eds) New Trends in Neural Computation. IWANN 1993. Lecture Notes in Computer Science, vol 686. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56798-4_212
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DOI: https://doi.org/10.1007/3-540-56798-4_212
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