Overlapping block PCA for face recognition

Combining Block-based PCA, Global PCA and LDA for Feature Extraction in Face Recognition

This paper presents a novel methodology for pattern classification, combining different feature extraction approaches, more precisely, global PCA, block-based PCA and LDA in order to improve the face classification performance. Block-based PCA is a new technique that is being widely used for feature extraction, especially in face recognition. Basically, the idea of block-based PCA is to first d...

Face Recognition using Eigenfaces , PCA and Supprot Vector Machines

This paper is based on a combination of the principal component analysis (PCA), eigenface and support vector machines. Using N-fold method and with respect to the value of N, any person’s face images are divided into two sections. As a result, vectors of training features and test features are obtain ed. Classification precision and accuracy was examined with three different types of kernel and...

Face Recognition using PCA, Deep Face Method

The performance process of face recognition involves the inspection study of facial features in an image, recognizing those features and comparing them to one of the many faces in the database. There are many algorithms capable of performing face recognition; such as: Principal Component Analysis, Discrete Cosine Transform, 3D recognition methods, Gabor Wavelets method etc. There were many issu...

Adaptive Modified PCA for Face Recognition

This paper presents a novel hybrid method for extracting license plates and recognizing characters from low-quality videos using morphological operations and Adaboost algorithm. First of all, the hybrid method uses the Adaboost algorithm for training a detector to detect license plates. This algorithm works well to detect license plates having lower intensities but fails to detect license plate...

Canonical Correlated PCA method For Face Recognition