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Search Results: 1 - 10 of 189871 matches for " G. Sainarayanan "
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Fast Complex Gabor Wavelet Based Palmprint Authentication
Jyoti Malik, Ratna Dahiya & G Sainarayanan
International Journal of Image Processing , 2011,
Abstract: A biometric system is a pattern recognition system that recognizes a person on the basis of thephysiological or behavioral characteristics that the person possesses. There is increasing interestof researchers in the development of fast and accurate personal recognition systems. In thispaper, Sliding window method is used to make the system fast by reducing the matching time.The reduction in computation time indirectly reduces the overall comparison time that makes thesystem fast. Here, 2-D Complex Gabor Wavelet method is used to extract features frompalmprint. The extracted features are stored in a feature vector and matched by hammingdistance similarity measurement using sliding window approach. Reduction of 74.12% and90.32% in comparison time is achieved using Sliding window methods. The improvement in timeis indicated by experimental results that makes a system rapid.
Wearable Real-Time Stereo Vision for the Visually Impaired
G. Balakrishnan,G. Sainarayanan,R. Nagarajan,Sazali Yaacob
Engineering Letters , 2007,
Statistical Models for Face Recognition System With Different Distance Measures
R.Thiyagarajan, S. Arulselvi, G.Sainarayanan
International Journal of Image Processing , 2011,
Abstract: Face recognition is one of the challenging applications of image processing.Robust face recognition algorithm should posses the ability to recognize identitydespite many variations in pose, lighting and appearance. Principle ComponentAnalysis (PCA) method has a wide application in the field of image processing fordimension reduction of the data. But these algorithms have certain limitations likepoor discriminatory power and ability to handle large computational load. Thispaper proposes a face recognition techniques based on PCA with Gaborwavelets in the preprocessing stage and statistical modeling methods like LDAand ICA for feature extraction. The classification for the proposed system is doneusing various distance measure methods like Euclidean Distance(ED), CosineDistance (CD), Mahalanobis Distance (MHD) methods and the recognition ratewere compared for different distance measures. The proposed method has beensuccessfully tested on ORL face data base with 400 frontal imagescorresponding to 40 different subjects which are acquired under variableillumination and facial expressions. It is observed from the results that use ofPCA with Gabor filters and features extracted through ICA method gives arecognition rate of about 98% when classified using Mahalanobis distanceclassifier. This recognition rate stands better than the conventional PCA and PCA+ LDA methods employing other and classifier techniques.
Fuzzy-Rule-Based Object Identification Methodology for NAVI System
R. Nagarajan,G. Sainarayanan,Sazali Yaacob,Rosalyn R. Porle
EURASIP Journal on Advances in Signal Processing , 2005, DOI: 10.1155/asp.2005.2260
Abstract: We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI) system. The NAVI has a single board processing system (SBPS), a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.
Journal of Engineering Science and Technology , 2008,
Abstract: A major drawback associated with the use of artificial neural networks for data mining is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the knowledge captured is not transparent and cannot be verified by domain experts. In this paper, Artificial Neural Network Tree (ANNT), i.e. ANN training preceded by Decision Tree rules extraction method is presented to overcome the comprehensibility problem of ANN. Two pruning techniques are used with the ANNT algorithm; one is to prune the neural network and another to prune the tree. Both of these pruning methods are evaluated to see the effect on ANNT in terms of accuracy, comprehensibility and fidelity.
International Journal of Engineering Science and Technology , 2011,
Abstract: In Digital video communication it is not practical, to store the full digital video without processing, because of the problems encountered in storage and transmission, so the processing technique called videocompression is essential. In video compression, one of the computationally expensive and resource hungry key element is the Motion Estimation. The Motion estimation is a process which determines the motion between two or more frames of video. In this paper, Four block matching motion estimation algorithms, namely Exhaustive Search (ES), Three Step Search (TSS), New Three Step Search (NTSS), and Diamond Search (DS) algorithms are compared and implemented for different distances between the frames of the video by exploiting the temporal correlation between successive frames of mristack and foreman slow motion videos and proved that Diamond Search (DS) algorithm is the best matching motion estimation algorithm that achieve best tradeoff between search speed (number of computations) and reconstructed picture quality with extensive simulation results and comparative analysis.
A Characterization of the Members of a Subfamily of Power Series Distributions  [PDF]
G. Nanjundan
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.26099
Abstract: This paper discusses a characterization of the members of a subfamily of power series distributions when their probability generating functions satisfy the functional equation where a, b and c are constants and is the derivative of f.
Double Negative Left-Handed Metamaterials for Miniaturization of Rectangular Microstrip Antenna  [PDF]
G. Singh
Journal of Electromagnetic Analysis and Applications (JEMAA) , 2010, DOI: 10.4236/jemaa.2010.26044
Abstract: In this paper, I have explored a significant concept for the miniaturization of microstrip patch antenna configuration by using the double negative (DNG) left-handed Metamaterials, which have dielectric permittivity and magnetic permeability both negative, simultaneously. It is achieved through the concept of phase-compensation by thin slab consist of the double positive (DPS) material, which have dielectric permittivity and magnetic permeability both positive, simultaneously and DNG metamaterials as a substrate of the microstrip patch antenna. By combining the DNG metamaterial slab with the slab made of DPS materials form a cavity resonator whose dispersion relation is independent of the sum of thickness of the slabs filling this cavity but it depends on the ratio of their thicknesses. This cavity constitutes by DPS and DNG material is used as substrate of the microstrip antennas and the DNG material slab is behave as phase compensator.
Dynamic and Configurational Approach to the Glass Transition by Nanoscale Cooperativity  [PDF]
G. Romeo
Open Journal of Biophysics (OJBIPHY) , 2012, DOI: 10.4236/ojbiphy.2012.23012
Abstract: Here we examine the findings obtained for disaccharide/water mixtures near glass transition that involves cooperative relaxation features on kinetic by viscosity and on thermodynamic behaviour by neutron scattering. Then to address cooperative phenomena that mitigate the Debye-Waller behaviour we invoke Adam-Gibbs’ idea of a cooperative rearranging region. Neutron results suggest that the excess mean square displacement behaves as free volume and is closely connected to an elementary step of the structural relaxation. Then viscosity data evidence a breakdown of the Einstein-Debye relation, decoupling attributed to the intermolecular cooperativity.
Confidence Level Estimator of Cosmological Parameters  [PDF]
G. Sironi
Journal of Modern Physics (JMP) , 2012, DOI: 10.4236/jmp.2012.329157
Abstract: Cosmological Models frequently suggest the existence of physical, quantities, e.g. dark energy, we cannot yet observe and measure directly. Their values are obtained indirectly setting them equal to values and accuracy of the associated model parameters which best fit model and observation. Apparently results are so accurate that some researchers speak of precision cosmology. The accuracy attributed to these indirect values of the physical quantities however does not include the uncertainty of the model used to get them. We suggest a Confidence Level Estimator to be attached to these indirect measurements and apply it to current cosmological models.
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