Principal Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the frequency domain between the input image and eigenvectors (weights). Simulation results show that the proposed implementation of PCA is faster than conventional one
—The development of image processing technologycurrently can alleviate human jobs, one of them as th...
Nowadays, face detection and recognition have gained importance in security and information access. ...
Principal component analysis (PCA) is an extensively used dimensionality reduction technique, with i...
Abstract: Principal Component Analysis (PCA) has many different important applications especially in...
In this paper, a new technique for fast painting with different colors is presented. The idea of pai...
A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and test...
A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and test...
This report presents the complete process of face recognition from theory to implementation and test...
Design and implementation of a fast parallel architecture based on an improved principal component a...
In this project, Principal Component Analysis (PCA), one of the methods in Facial Recognition will b...
Face detection system attracts huge attention in recent years due to it may improve security of surv...
This paper mainly addresses the building of not only pose but also size independent face recognition...
A kernel principal component analysis (PCA) was recently proposed as a nonlinear extension of a PCA....
Abstract:- Face recognition is a biometric technology with a wide range of potential applications su...
Abstract Principal Component Analysis PCA is an eigen-based technique popularly employed in redundan...
—The development of image processing technologycurrently can alleviate human jobs, one of them as th...
Nowadays, face detection and recognition have gained importance in security and information access. ...
Principal component analysis (PCA) is an extensively used dimensionality reduction technique, with i...
Abstract: Principal Component Analysis (PCA) has many different important applications especially in...
In this paper, a new technique for fast painting with different colors is presented. The idea of pai...
A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and test...
A face recognition algorithm based on Principal Component Analysis (PCA) has been developed and test...
This report presents the complete process of face recognition from theory to implementation and test...
Design and implementation of a fast parallel architecture based on an improved principal component a...
In this project, Principal Component Analysis (PCA), one of the methods in Facial Recognition will b...
Face detection system attracts huge attention in recent years due to it may improve security of surv...
This paper mainly addresses the building of not only pose but also size independent face recognition...
A kernel principal component analysis (PCA) was recently proposed as a nonlinear extension of a PCA....
Abstract:- Face recognition is a biometric technology with a wide range of potential applications su...
Abstract Principal Component Analysis PCA is an eigen-based technique popularly employed in redundan...
—The development of image processing technologycurrently can alleviate human jobs, one of them as th...
Nowadays, face detection and recognition have gained importance in security and information access. ...
Principal component analysis (PCA) is an extensively used dimensionality reduction technique, with i...