Classification of MR medical images Based Rough-Fuzzy KMeans
Ahmed Mohamed Elmoasry · IOSR Journal of Mathematics · 2017
Image classification is very significant for many vision of computer and it has acquired significant solicitude from industry and research over last years.We, explore an algorithm via the approximation of Fuzzy -Rough-K-means (FRKM), to bring to light data reliance, data decreasing, estimated of the classification (partition) of the set, and induction of rule from databases of the image.Rough theory provide a successful approach of carrying on precariousness and furthermore applied for image classification feature similarity dimensionality reduction and style categorization.The suggested algorithm is derived from a k means classifier using rough theory for segmentation (or processing) of the image which is moreover split into two portions.Exploratory conclusion output that, suggested method execute well and get better the classification outputs in the fuzzy areas of the image.The results explain that the FRKM execute well than purely using rough set, it can get 94.4% accuracy figure of image classification that, is over 88.25% by using only rough set.