Abstract
A solely excitatory oscillator network (SEON) is proposed for color image segmentation. SEON utilizes its parallel nature to reliably segment images in parallel. The segmentation speed does not decrease in a very large network. Using NBS distance, SEON effectively segments color images in term of human perceptual similarity. Our model obtains an average segmentation rate of over 98.5%. It detects vague boundaries very efficiently. Experiments show that it segments faster and more accurately than other contemporary segmentation methods. The improvement in speed is more significant for large images.
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© 2004 Springer-Verlag Berlin Heidelberg
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Li, C.L., Lee, S.T. (2004). Solely Excitatory Oscillator Network for Color Image Segmentation. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks - ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3174. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28648-6_61
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DOI: https://doi.org/10.1007/978-3-540-28648-6_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22843-1
Online ISBN: 978-3-540-28648-6
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