Artificial Neural Networks

Artificial Neural Networks

ABSTRACT:

Face Recognition is the inherent capability of human beings. Identifying a person by face is one of the most fundamental human functions since time immemorial. Face recognition by computer is to endow a machine with capability to approximate in some sense, a similar capability in human beings. To impart this basic human capability to a machine has been a subject of interest over the last few years. Such a machine would find considerable utility in many commercial transactions, personal management, security and the law enforcement applications, especially in criminal identification, authentication in secure system etc. Enough research has not been carried out on identification of human faces. However a number of automated or semi-automated recognition studies have been reported.

Artificial Neural Networks (ANN) is an attempt to simulate human brain; hence this method is named artificial neural networks. Neural networks, which are inspired from the studies of biological nervous systems, have recently been used for various applications, due to the distributed computing fashion over a large number of simple processing units (Neurons). These neurons of nodes, which are simple, non-linear computational elements, are connected by links with variable weights. The inherent parallelism of these networks provides high computational rates with greater degree of robustness or fault tolerance than conventional computers. The fault tolerance is due to the presence of many processing nodes, each of which is responsible for a small portion of the task. Damage to a few nodes or links, doesn’t impair overall performance significantly.

Introduction:

Identifying a person by his face is one of the most fundamental human functions since time immemorial. To impart this basic human capability to machine has been a subject of interest over the last few years. Such a machine would find considerable utility in many commercial tractions, personnel management and security and law enforcement application, specially in criminal identification, authentication in secure system etc. Enough research has not been carried out on identification of human face. Recently however a number of automated recognition are mainly two folds.

• Large number of facial patterns (faces to be recognized are finitely very large) contrary to many pattern recognition problems where the numbers of pattern classes are finite.

• The dissimilarity amongst the facial patterns is inherently very small.

Recent research effort has been directed towards the extraction of features from the frontal facial photographs of human and its economical use in machine identification of human faces. This strategy best suited is to get the outline of the profile and extract discrete features from it. This technique has been used by L.D. Hardmonetal for the recognition of human faces.


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