Abstract
Change Detection plays an important role in detecting various kinds of dissimilarities between two images of the same object over a period of time. This has extensive use in medical imaging and remote sensing. We propose a method of change detection where we first apply a change vector analysis (CVA), then apply clustering on the image by Rough C-means (RCM) and finally threshold it to obtain the Difference image (DI). RCM provides the concepts of upper approximation n and lower approximation which lead to better clustering and decrease the error rate. Experimental results of the proposed method are compared with existing change detection algorithms and it has been found to perform evidently better than the others.
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Halder, A., Saha, K., Sarkar, A., Sen, A. (2019). A Change Detection Technique Using Rough C-Means on Medical Images. In: Mallick, P., Balas, V., Bhoi, A., Zobaa, A. (eds) Cognitive Informatics and Soft Computing. Advances in Intelligent Systems and Computing, vol 768. Springer, Singapore. https://doi.org/10.1007/978-981-13-0617-4_19
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DOI: https://doi.org/10.1007/978-981-13-0617-4_19
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