Abstract
In this article we propose a modification to the HMRF-EM framework applied to image segmentation. To do so, we introduce a new model for the neighborhood energy function of the Hidden Markov Random Fields model based on the Hidden Markov Model formalism. With this new energy model, we aim at (1) avoiding the use of a key parameter chosen empirically on which the results of the current models are heavily relying, (2) proposing an information rich modelisation of neighborhood relationships.
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Sublime, J., Cornuéjols, A., Bennani, Y. (2014). A New Energy Model for the Hidden Markov Random Fields. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8835. Springer, Cham. https://doi.org/10.1007/978-3-319-12640-1_8
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DOI: https://doi.org/10.1007/978-3-319-12640-1_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-12639-5
Online ISBN: 978-3-319-12640-1
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