Abstract
This research paper focuses on image segmentation by random fields generated by using MRF energy level set function. The focus of the researcher is on this technique of how MRF energy is embedded in the standard level set energy method. The connection among all the pixels and its neighborhood is established by MRF energy function, and it attempts to have all the pixels in the same region. Comparing the MRF level set technique with surviving manifold learning technique on different standard images. In comparison, the proposed technique is fast and healthy for image segmentation tough the statistical tables present the researcher the superiority of the proposed technique.
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Pemula, R., Nagaraju, C. (2019). Generation of Random Fields for Image Segmentation Based on MRF Energy Level Set Method. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 104. Springer, Singapore. https://doi.org/10.1007/978-981-13-1921-1_53
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DOI: https://doi.org/10.1007/978-981-13-1921-1_53
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