Of the problem areas, the domain of matching complex objects has received, by far, the most attention. This research work is concerned with the specific class of complicated objects, i.e. logo. The progress, particularly in this field, is still at extensive research work level, due to infinite varieties of shapes and classes which are used. Essentially, the algorithm proposed is based on Princi...

This paper presents a face localization and tracking algorithm which is based upon skin color detection and principle component analysis (PCA) based eye localization. Skin color segmentation is performed using statistical models for human skin color. The skin color segmentation task results in a mask marking the skin color regions in the actual frame, which is further used to compute the positi...

Principle component analysis (PCA) is commonly used to compute a bounding box of a point set in Rd . The popularity of this heuristic lies in its speed, easy implementation and in the fact that usually, PCA bounding boxes quite well approximate the minimum-volume bounding boxes. In this paper we give a lower bound on the approximation factor of PCA bounding boxes of convex polytopes in arbitrar...

In this paper, a review on the latest methodologies and application of the Principle Component Analysis (PCA) has been done in the area of image processing. Exploring basic theory of multivariate analysis, which involves a mathematical procedure to transform a number of correlated variables into a number of uncorrelated variables have been studied, compared and analyzed for better performance. ...

This paper proposes the noble multimodal biometric system using multiple biometric traits such as face, ear and finger. This combination of multimodal traits is unique combination offering a better authenticity and accuracy than the existing multimodal biometric systems. In this experimentation the discrete wavelet transforms (DWT) is used for extraction of features which is followed by the pri...

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA nu...

In this paper we compare the quality of three different principle component analysis (PCA) based methods to generate transfer functions for the 3D visualization of imaging spectroscopy data. We discuss three criteria for judging the quality of features in these visualizations. These criteria are used to interpret visualizations of features in the brain of the snail Lymnaea Stagnalis. We show th...

In face recognition feature extraction and classification are the two aspects to be focused. In principle component analysis (PCA) based face recognition technique, the 2D face image matrices must be previously transformed in to one dimensional image vectors. In this paper two dimensional principle component analysis(2DPCA) is used to extract the features. Comparing to conventional principle co...

Principle Component Analysis (PCA) and Independent Component Analysis (ICA) were used to decompose the fMRI time series signal and separate the BOLD signal change from the structured and random noise. Rather than using component analysis to identify spatial patterns of activation and noise, the approach we took was to identify PCA or ICA components contributing primarily to the noise. These noi...