K. Manikantan

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Face recognition (FR) with reduced number of features is challenging and energy based feature extraction is an effective approach to solve this problem. However, existing methods are hard to extract only the required low frequency features, which is important for capturing the intrinsic features of a face image. This paper proposes a novel Block-Based(More)
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)
Feature Selection is an optimization problem in any Face Recognition technology. This paper proposes a novel method of Binary Particle Swarm Optimization called Accelerated Binary Particle Swarm Optimization (ABPSO) by intelligent acceleration of particles. Together with Image Pre-processing techniques such as Resolution Conversion, Histogram Equalization(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)