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Home / programming language / Online Matlab Projects / Rain drop Detection and Removal using K-Means Clustering
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Rain drop Detection and Removal using K-Means Clustering

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SKU: PROJ8413 Categories: 2018-2019 Projects, Digital Image Processing Projects, Online Matlab Projects Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Matlab Project, PHP Project, Students Projects
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Rain drop Detection and Removal using K-Means
Clustering

Abstract-At the first place ,a novel hybrid algorithm has been proposed to detect raindrops , remove and then restore the image back ground in a single image. In addition, this new hybrid algorithm is framed based on K-Means clustering and Median filtering for the fast retrieval of Rain droplets from the single image. KMeans clustering algorithm is an efficient algorithm for image clustering.At the same time, the algorithm proposed has different approach from other established numerical schemes. The hybrid algorithm is framed in order to identify the rain droplets using clustering and shape modeling of raindrops. The proposed system is fast compared with alternate droplet identification schemes. The process allows rapid evaluation of the contour of the raindrops and convergence to its final resultant with very little iteration. finally, the experiments demonstrate the efficiency and accuracy of the method.

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