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4 articles for “Discrete Hidden Markov Model”
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Retina Recognition System using PCA-based Discrete Hidden Markov Model
Abstract: In this paper, a unique approach of retina recognition system has been proposed. Principal component analysis based dimensionality reduction technique has been used here and discrete hidden Markov model (DHMM) has been applied to classify the retinal images. The retinal images are taken from DRIVE retina database. Then some image pre-processing techniques such as image scaling, median filtering-based noise reduction and edge-detection techniques have been used to ready the retinal …
Published in Journal Of Network security · Vol. 3, Issue 1, 2015 · pp. 28–32 Read article
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Discrete Hidden Markov Model based Face Recognition System Introducing Sustainability of Uneven Lighting Distortion
Abstract: The aim of this work is to enhance the performance of appearance based face recognition system to remove the uneven lighting effect which is generally occurred in natural environment. Active Shape Model has been used to detect the facial shape and contrast based edge detection technique has been applied to reduce the uneven lighting problem. Linear Discriminant Analysis has been used to reduce the dimension of the facial feature vector. …
Published in Trends in Electrical Engineering · Vol. 4, Issue 1, 2014 · pp. 9–16 Read article
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Multi-Modal Iris and Retina Recognition System using Discrete Hidden Markov Model based Score Fusion Technique
Abstract: The contribution of this work is to propose a model of multi-modal iris and retina recognition system where Hidden Markov Model based score fusion technique has been used for decision fusion approach. Two different uni-modal techniques such as iris recognition and retina recognition outputs are combined by using baseline reliability ratio based score fusion technique. CASIA iris dataset and DRIVE retinal dataset have been used to acquire the iris and …
Published in Current Trends in Information Technology · Vol. 5, Issue 2, 2015 · pp. 7–12 Read article
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Face and Iris based Multimodal Person Identification using Likelihood Ratio Score Fusion Approach.
Abstract: AbstractThe aim of this paper is to propose a multimodal biometric system where likelihood ratio score fusion technique has been used to combine face and iris uni-modal biometric system outputs. Active Shape Model (ASM) has been used to extract the facial features and standard methods have been applied to effectively extract the human iris features. To evaluate the output of each individual modality of face and iris, Discrete Hidden Markov …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 3, 2015 · pp. 60–67 Read article