Ramesh Rayudu

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Introducing methods that can work out the problem of noisy image segmentation is necessary for real-world vision problems. This paper proposes a new computational algorithm for segmentation of gray images contaminated with impulse noise. We have used Fuzzy C-Means (FCM) in fusion with Particle Swarm Optimization (PSO) to define a new similarity metric based(More)
The necessity of proposing algorithms that are effective in noisy image segmentation is clear in many real-world applications. This paper proposes a new algorithm for severely noisy image segmentation by looking at the proper choice of feature, and feature manipulation. We are using Discrete Wavelet Transformation (DWT) as a tool to provide our method with(More)
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