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Many traditional binarization techniques fail to overcome the challenging impediments fostered by degraded historical handwritten document images. In this paper, we present a fast and competent, yet simple binarization technique that uses a Fuzzy C-Means based global thresholding approach, aided by background separation. The proposed method uses a superset of foreground regions to correctly assess background of the document image. Background is estimated based on a sliding interpolation window of variable dimension, judged by appraising the nature of text stroke. Ultimately a global approach is undertaken to binarize the background-separated normalized and enhanced image by clustering the pixels using Fuzzy C-Means. This helps considering indeterministic nature of each pixel and the bland nature of the normalized image. The proposed technique is applied on the most recent (2016 …