In this paper, recognition system for totally unconstrained handwritten characters for south Indian language of Kannada is proposed. The proposed feature extraction technique is based on Fourier Transform and well known Principal Component Analysis (PCA). The system trains the appropriate frequency band images followed by PCA feature extraction scheme. For subsequent classification technique, P...

In this paper, we have presented a system for isolated curved Gurmukhi character recognition using projection of gradient. We have used projection of gradient features to extract the features of the character. The method relies upon the application of a projection based feature extraction using Radon transform, on both the original image and a set of produced images corresponding to different g...

A real time human activity recognition system based on Radon transform (RT), Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) is presented. RT improves low frequency components and PCA provide global representation of these low frequency components in few eigenvectors. The proposed technique computes radon projections in different directions to obtain directional featur...

Due to being so effective to mitigate the fading effect of wireless channels relay networks have received so much attention recently. Especially because relays are typically small, power limited and low cost and also can remove the problem of attenuation of signal due to propagation loss. Moreover increasing the number of relays improves the system performance and also using more power. The sys...

Human faces are major identity mark. Face recognition is the active research area in real time applications. Face detection has many applications in biometrics, video surveillance , robotics, control of manmachines, photography, and image indexing. Many face recognition techniques are developed to recognize human features. In this paper the study and methodology of PCA (Principal Component Anal...

In this paper, we present a compression framework, for molecular dynamics (MD) simulation data, which yields significant performance by combining the strength of principal component analysis (PCA) and discrete cosine transform (DCT). Though it is a lossy compression technique, the effect on analytics performed on decompressed data is very minimal. Compression ratio up to 13 is achieved with acc...

This paper studies the application of principal component analysis, multiple polynomial regression, and artificial neural network ANN techniques to the quantitative analysis of binary mixture of dye solution. The binary mixtures of three textile dyes including blue, red and yellow colors were analyzed by PCA-Multiple polynomial Regression and PCA-Artificial Neural network PCA-ANN methods. The o...

p2x 7 antagonist activity for a set of 49 molecules of the p2x 7 receptor antagonists, derivatives of purine, was modeled with the aid of chemometric and artificial intelligence techniques. the activity of these compounds was estimated by means of combination of principal component analysis (pca), as a well-known data reduction method, genetic algorithm (ga), as a variable selection technique, ...

the study area covers the northern part of the baft geological map (scale of 1:100 000 ). several porphyry and vein-type mineralization are reported from this area. a topic that is discussed in the mineral exploration community is the use of remote sensing and airborne geophysics for porphyry type mineralization. which one is more reliable and efficient in hydrothermal alteration mapping? airbo...

acoustic analysis is a proper method in vocal fold pathology diagnosis so that itcan complement and in some cases replace the other invasive, based on direct vocalfold observation, methods. there are different approaches and algorithms for vocalfold pathology diagnosis. these algorithms usually have three stages which arefeature extraction, feature reduction and classification. in this paper in...