Biometrics based recognition is always being the most versatile and demanding method for the security implementation.since 50s scientist working on many human factors which could be used for the authentication.Majorly,the face photograph is used for the verification of the person and the major areas of use are National Identity Card,Passport,Driving Licenses etc etc.
In the late 90s when computer has been evolved upto great extent that it covers almost every field of life,authentication and accurate verification also became a great need of each & every department and organization.
After the success of Fingerprint recognition,The next Step was the Face Recognition technology.
Many approaches are introduced for the face detection and recognition on which many of the research department spent a huge amount to get the best out if it.
In computer science,we are lucky enough to use mathematical and statistical methods for the face detection & recognition.One of the most widely used technique is PCA based Face recognition which clams to give the 70-90% of the accurate results.
PCA stands for the Principal Component analysis which is basically used for the dimensional reduction or compression of data into meaningful parameters.Typically,when dealing with very large amount of data,PCA is always preferred over other technique due to its simplicity and accuracy.
Another remarkable benefit of this technique is its less demand for processing power if we are using computers for the calculation and even in case new entity or person is required to add in training set,it provides a robust method which results in fast training and then recognition.
In other techniques,if new person is required to add,then whole network need to calculate the parameters from 1st person to last one which required lots of processing and time.
In the late 90s when computer has been evolved upto great extent that it covers almost every field of life,authentication and accurate verification also became a great need of each & every department and organization.
After the success of Fingerprint recognition,The next Step was the Face Recognition technology.
Many approaches are introduced for the face detection and recognition on which many of the research department spent a huge amount to get the best out if it.
In computer science,we are lucky enough to use mathematical and statistical methods for the face detection & recognition.One of the most widely used technique is PCA based Face recognition which clams to give the 70-90% of the accurate results.
PCA stands for the Principal Component analysis which is basically used for the dimensional reduction or compression of data into meaningful parameters.Typically,when dealing with very large amount of data,PCA is always preferred over other technique due to its simplicity and accuracy.
Another remarkable benefit of this technique is its less demand for processing power if we are using computers for the calculation and even in case new entity or person is required to add in training set,it provides a robust method which results in fast training and then recognition.
In other techniques,if new person is required to add,then whole network need to calculate the parameters from 1st person to last one which required lots of processing and time.
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