Dilip Senapati

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Image thresholding is one of the most widely used segmentation techniques in image processing. The objective of image thresholding is to segment a given image so that the object is more distinguishable from its background. This has been an active area of research in image processing and several methods have been proposed. Some of them are based on entropy(More)
Understanding stock market dynamics is a challenging problem. We have proposed a novel approach for Black-Scholes model with periodic interest rate using Monte Carlo simulation. In this paper, we have also analyzed the First Passage Time (FPT) distribution under some given strike price. We have applied Monte Carlo simulation to the underlying Stochastic(More)
Segmentation of an image is an important area of research in image processing. There are various techniques proposed for image segmentation. One of the most widely used segmentation techniques is based on thresholding. In this paper, we present a thresholding technique based on entropy for noisy images. Two noises ‘Gaussian’ and ‘Poisson’ have been(More)
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