Abstract
We propose a method that uses k-mean clustering and Random walk algorithm for image segmentation. The use of the random walk algorithm is widespread as it segments thin and elongated parts and can produce a complete division of the image. However if there is any minute discontinuity the unwanted part may get segmented. To avoid this we first partition the image into group of clusters then apply random walk algorithm. Comparing the results of segmented image with clustering and without clustering it is shown that the proposed algorithm is most effective.
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Mohebbanaaz, Sirisha, M., Joseph Rajiv, K. (2020). Random Walk with Clustering for Image Segmentation. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-030-24318-0_1
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DOI: https://doi.org/10.1007/978-3-030-24318-0_1
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