S
S. Srinivas Kumar
Researcher at Jawaharlal Nehru Technological University, Kakinada
Publications - 59
Citations - 829
S. Srinivas Kumar is an academic researcher from Jawaharlal Nehru Technological University, Kakinada. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 14, co-authored 57 publications receiving 702 citations. Previous affiliations of S. Srinivas Kumar include University College of Engineering & Indian Institute of Technology Kharagpur.
Papers
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A Robust Image Watermarking Scheme using Singular Value Decomposition
TL;DR: This paper presents a robust image watermarking scheme for multimedia copyright protection that is more secure and robust to various attacks, viz., JPEG2000 compression, JPEG compression, rotation, scaling, cropping, row-column blanking, rows-column copying, salt and pepper noise, filtering and gamma correction.
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Medical Image Segmentation Algorithms using Deformable Models: A Review
TL;DR: Various approaches of medical image segmentation, available algorithms for deformable models are reviewed and their advantages, disadvantages, and limitations are discussed.
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Content Based Image Retrieval Using Exact Legendre Moments and Support Vector Machine
TL;DR: CBIR system using Exact Legendre Moments (ELM) for gray scale images is proposed in this work, and Superiority of the proposed CBIR system is observed over other moment based methods in terms of retrieval efficiency and retrieval time.
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Feature Selection Using Relative Fuzzy Entropy and Ant Colony Optimization Applied to Real-time Intrusion Detection System
TL;DR: Fuzzy Entropy based heuristic for Ant Colony Optimization (ACO) in-order to search for global best smallest set of network traffic features for Real-Time Intrusion Detection Data set is proposed.
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Content Based Image Retrieval Using Exact Legendre Moments and Support Vector Machine
TL;DR: In this paper, an orthogonal moment based CBIR system using exact Legendre Moments (ELM) for gray scale images is proposed, which can represent image shape features compactly.