V. Vaithiyanathan

Indira Gandhi Centre for Atomic Research, SASTRA University

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About

V. Vaithiyanathan’s research lies at the intersection of digital image processing, robotics, and intelligent navigation systems. His work focuses on developing computational methods for image segmentation, path planning, and autonomous vehicle guidance. In his most cited paper, “Analysis of Image Segmentation for Radiographic Images” (2012, 18 citations), he systematically evaluated five segmentation techniques—region growing, watershed, thresholding, split and merge, and k-means clustering—providing a foundational reference for medical image analysis. He further advanced robotics with “Layered Approach for Three Dimensional Collision Free Robot Path Planning using Genetic Algorithm” (2015, 5 citations), where he introduced a layered decomposition strategy to solve optimal, collision-free navigation in 3D static environments using genetic algorithms. His work on “Study of Feature based Image Registration Algorithms for Navigation of Unmanned Aerial Vehicles” (2015, 4 citations) surveyed key registration methods essential for object recognition and terrain change detection. Collectively, Vaithiyanathan’s contributions bridge image analysis and autonomous systems, offering practical frameworks for both medical imaging and UAV navigation—work that continues to inform researchers in computer vision and intelligent robotics.