K. Manikantan

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This paper proposes a novel Discrete Cosine Transform (DCT) spectrum based approach to enhance the performance of a face recognition (FR) system employing a unique astroid shaped feature selection from the DCT spectrum. Individual stages of the FR system are examined and an attempt is made to improve each stage. A Binary Particle Swarm Optimization(More)
Face Recognition (FR) under varying lighting conditions is challenging and exacting illumination invariant features is an effective approach to solve this problem. In this paper, we propose a novel illumination normalization method called Histogram based Dynamic Gamma Intensity Correction, HDGIC, wherein the value of Λ is made to vary dynamically(More)
Face recognition under varying occlusions and lighting conditions is challenging, and exacting occlusion and illumination invariant features is an effective approach to solve this problem. In this paper, we propose two novel techniques viz., <i>DWT Thresholding</i> and <i>Laplacian-Gradient Masking</i>, to improve the performance of a face recognition(More)
Ear detection in facial images under varying pose, background and occlusion is a challenging issue. This paper proposes an entropy-cum-Hough-transform-based approach for enhancing the performance of an ear detection system, employing the unique combination of hybrid ear localizer (HEL) and ellipsoid ear classifier (EEC). By exploiting the entropic(More)
Particle Swarm Optimization (PSO), limited by the Exploration-Exploitation balance problem is challenging. Exploring more search space and fast convergence is an effective approach to solve this problem. In this paper, we propose a novel PSO algorithm called K-Nearest-Neighbour Motivation PSO, KNN-M-PSO, which provides a promising solution to this problem.(More)
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