Abstract
The aim of image segmentation is the partition of the image in homogeneous regions. In this paper we propose an approximation based on Markov Random Fields (MRF) able to perform correct segmentation in real time using colour information. In a first approximation a simulated annealing approach is used to obtain the optimal segmentation. This segmentation will be improved using an adaptive threshold algorithm, to achieve real time. The experiment results using the proposed segmentation prove its correctness, both for the obtained labelling and for the response time.
This work has been financed by the Generalitat Valenciana project GV04B685.
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Arques, P., Aznar, F., Pujol, M., Rizo, R. (2006). Real Time Image Segmentation Using an Adaptive Thresholding Approach. In: Marín, R., Onaindía, E., Bugarín, A., Santos, J. (eds) Current Topics in Artificial Intelligence. CAEPIA 2005. Lecture Notes in Computer Science(), vol 4177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881216_41
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DOI: https://doi.org/10.1007/11881216_41
Publisher Name: Springer, Berlin, Heidelberg
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