Abstract
An unsupervised approach to image segmentation which fuses different sources of information is presented. The proposed approach takes advantage of the combined use of 3 different strategies: an appropriated placement, the control of decision criterion, and the results refinement. The new algorithm uses the boundary information to initialize a set of active regions which compete for the pixels in order to segment the whole image. The method is implemented on a multiresolution representation which ensures noise robustness as well as computation efficiency. The accuracy of the segmentation results has been proven through an objective comparative evaluation of the method.
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Muñoz, X., Freixenet, J., Cufí, X., Martí, J. (2002). Region-Boundary Cooperative Image Segmentation Based on Active Regions. In: Escrig, M.T., Toledo, F., Golobardes, E. (eds) Topics in Artificial Intelligence. CCIA 2002. Lecture Notes in Computer Science(), vol 2504. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36079-4_32
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DOI: https://doi.org/10.1007/3-540-36079-4_32
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