Abstract
In this paper, the authors have proposed an algorithm of segmenting grayscale image using associative memories approach. The algorithm is divided in three steps. In the first step, a set of regions (classes), where each one groups to a certain number of pixel values, is obtained. In the second step, the associative memories training phase is applied to the information obtained from first phase and an associative network, that contains the centroids group of each of the regions in which the image will be segmented, is obtained. Finally, using the associative memories classification phase, the centroid to which each pixel belongs is obtained and the image segmentation process is completed.
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Guzmán, E., Jiménez, O.M.C., Pérez, A.D., Pogrebnyak, O. (2011). Using Associative Memories for Image Segmentation. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21111-9_44
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DOI: https://doi.org/10.1007/978-3-642-21111-9_44
Publisher Name: Springer, Berlin, Heidelberg
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