Abstract
Image segmentation is a long existing problem and still regarded as unsolved to a large extent in computer vision. This letter describes the modeling method of competitive neural networks and elucidates its connection with the Hopfield type optimization network. A new algorithm to map the image segmentation problem onto competitive networks is proposed and its convergence is shown by the stability analysis. Finally, the improvement on the competitive neural networks based method is validated by the simulation results.
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© 2006 Springer-Verlag Berlin Heidelberg
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Yan, R., Er, M.J., Tang, H. (2006). An Improvement on Competitive Neural Networks Applied to Image Segmentation. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_73
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DOI: https://doi.org/10.1007/11760023_73
Publisher Name: Springer, Berlin, Heidelberg
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