scispace - formally typeset
Proceedings ArticleDOI

Face Recognition System using Artificial Neural Networks Approach

Reads0
Chats0
TLDR
A face recognition system based on recent method which concerned with both representation and recognition using artificial neural networks is presented and produces promising results for face verification and face recognition.
Abstract
Advances in face recognition have come from considering various aspects of this specialized perception problem. Earlier methods treated face recognition as a standard pattern recognition problem; later methods focused more on the representation aspect, after realizing its uniqueness using domain knowledge; more recent methods have been concerned with both representation and recognition, so a robust system with good generalization capability can be built by adopting state-of-the-art techniques from learning, computer vision, and pattern recognition. A face recognition system based on recent method which concerned with both representation and recognition using artificial neural networks is presented. This paper initially provides the overview of the proposed face recognition system, and explains the methodology used. It then evaluates the performance of the system by applying two (2) photometric normalization techniques: histogram equalization and homomorphic filtering, and comparing with euclidean distance, and normalized correlation classifiers. The system produces promising results for face verification and face recognition

read more

Citations
More filters
Journal ArticleDOI

Face Recognition: A Survey

TL;DR: Several applications of a face recognition system such as video surveillance, Access Control, and Pervasive Computing has been discussed and a detailed overview of some important existing methods used to dealing the issues of face recognition have been presented.
Proceedings ArticleDOI

Automatic Face Recognition System by Combining Four Individual Algorithms

TL;DR: A face recognition systems based on one combination of four individual techniques namely Principal Component Analysis (PCA), Discrete Cosine Transform (DCT), Template Matching using Corr and Partitioned Iterative Function System (PIFS), which fuse the scores of all of these four techniques in a single face recognition system.
Journal ArticleDOI

Localization of Mobile Sensors and Actuators for Intervention in Low-Visibility Conditions: The ZigBee Fingerprinting Approach

TL;DR: This paper focuses on the Zigbee fingerprinting localization method used to obtain the position of the mobile sensors and actuators by training a database of radio signals for each scenario, demonstrating the feasibility of the method for a real emergency intervention.
Journal ArticleDOI

Evaluating the Performance of Face Sketch Generation using Generative Adversarial Networks

TL;DR: This article presents a methodology for generating a colored photo from a sketch, which can be used for identification using a variety of classification techniques, and achieves a minimum average rate of 65% similarity index value on all employed datasets.
Journal ArticleDOI

Face Recognition and Verification Using Artificial Neural Network

TL;DR: A face recognition system based on recent method which concerned with both representation and recognition using artificial neural networks is presented and evaluates the performance of the system by applying two photometric normalization techniques: histogram equalization and homomorphic filtering.
References
More filters
Proceedings Article

Distance Metric Learning for Large Margin Nearest Neighbor Classification

TL;DR: In this article, a Mahanalobis distance metric for k-NN classification is trained with the goal that the k-nearest neighbors always belong to the same class while examples from different classes are separated by a large margin.
Journal ArticleDOI

Face recognition: a convolutional neural-network approach

TL;DR: A hybrid neural-network for human face recognition which compares favourably with other methods and analyzes the computational complexity and discusses how new classes could be added to the trained recognizer.
Posted Content

A Tutorial on Principal Component Analysis.

TL;DR: This manuscript focuses on building a solid intuition for how and why principal component analysis works, and crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA.
Journal ArticleDOI

Recognizing faces with PCA and ICA

TL;DR: It is able to show that the FastICA algorithm configured according to ICA architecture II yields the highest performance for identifying faces, while the InfoMax algorithm configurations is better for recognizing facial actions.
Journal ArticleDOI

Total variation models for variable lighting face recognition

TL;DR: The logarithmic total variation (LTV) model is presented, which has the ability to factorize a single face image and obtain the illumination invariant facial structure, which is then used for face recognition.
Related Papers (5)