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Iris Recognition (IR) under varying contrast and live-tissues is challenging. This paper proposes two novel techniques viz., Radon Transform Thresholding (RTT) and Gradient-based Isolation (GI). RTT is used to extract the prominent features from the pre-processed image. GI is a pre-processing technique which uses the edge detection property of Gradient(More)
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 Digital Watermarking Algorithm using a unique combination of Discrete Wavelet Transform (DWT), Discrete Fourier Transform (DFT) and Singular Value Decomposition (SVD) for secured transmission of data through watermarking digital color images. The singular values obtained from SVD of DWT+DFT transformed watermark is embedded onto the(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)
Face Recognition (FR) under varying background conditions is challenging, and exacting background invariant features is an effective approach to solve this problem. In this paper, we propose a novel method for background removal based on the k-means clustering algorithm, which lays the ground for DWT-based feature extraction to enhance the performance of a(More)
Feature Extraction plays a very important role in Face Recognition technology. This paper proposes a novel Discrete Cosine Transform (DCT) fusion technique based on facial symmetry. Also proposed are DCT subset matrix selection based on aspect ratio of the image and pre-processing concepts, namely Local Histogram Equalization to remove illumination(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)