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INTRODUCTION Face recognition is one of the pattern recognition systems. Pattern recognition can be defined as the categorization of input data into identifiable classes Face recognition is capable of extracting and picking up faces from the crowd and have it compared to an image source - database. The software has the ability to know how the basic human face looks like in order for it to work accordingly.

reasons to choose face recognition. :

reasons to choose face recognition. no physical interaction on behalf of the user. More accurate and allows for high enrolment and verification rates. not require an expert to interpret the comparison result. It can use your existing hardware infrasrastructure(camaras)


COMPONENTS OF FACE RECOGNITION SYSTEMS An automated mechanism that scans and captures a digital or an analog image of a living personal characteristics.(enrollment module) Another entity which handles compression, processing, storage and compression of th (database) The third interfaces with the application system ( identification module) User interface captures the analog or digital image of the person's face


Face Two types of camprisons Verifacation - compares the given individual and gives a yes or no decision. Identification - compares the given individual to all the Other individuals in the database All identification or authentication technologies operate using the following four stages: capture extaraction comparison match /non match

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Capture: A physical or behavioural sample is captured by the system during Enrollment and also in identification or verification process Extaraction: : unique data is extracted from the sample(code) Comparison: compared with a new sample match /non match: the system decides if the features extracted from the new samples are a match or a non match Face recognition technology analyze the unique shape, pattern and positioning of the facial features. It starts with a picture, attempting to find a person in the image. locate head and eye position A matrix is then developed based on the characteristics of the Individual face . (eye mouth and nosrils).


IMPLEMENTATION OF FACE RECOGNITION TECHNOLOGY following stages: Data acquisition Input processing Face image classification and decision making

Data acquisition:

Data acquisition The input can be recorded as video A sample of 1 sec duration consists of a 25 frame video sequence. More than one camera can be used to produce a 3D representation It help to protect against the usage of photographs to gain unauthorized access.

Input processing: :

Input processing: A pre-processing module locates the eye position and takes care of the surrounding lighting condition and colour variance. Once the face is detected, it must be localized and Normalization The appearance of the face can change considerably during speech and due to facial expressions.


HOW FACE RECOGNITION SYSTEMS WORK Facial recognition software is based on the ability to first recognize faces, which is a technological feat in itself. Nodal point :- certain distinguishable landmarks. There are about 80 nodal points on a human face. Here are few nodal points that are measured by the software. distance between the eyes width of the nose depth of the eye socket cheekbones jaw line chin These nodal points are measured to create a numerical code, a string of numbers that represents a face in the database. This code is called faceprint. Only 14 to 22 nodal points are needed for Detecting face and complete the recognition process


THE SOFTWARE Detection eye detection face detection

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Alignment: Once a face is detected, the system determines the head's position, size and pose. A face needs to be turned at least 35 degrees toward the camera for the system to register it. Normalization: Normalization is performed regardless of the head's location and distance from the camera Representation : This coding process allows for easier comparison of the newly acquired facial data to stored facial data Matching: The newly acquired facial data is compared to the stored data


Advantages: Social acceptability easy to use inexpensive Can findout the face even in crowd

Disadvantages :

Disadvantages Face recognition systems cannot tell the difference between identical twins A face needs to be well lighted by controlled light sources in automated face authentication systems.


conclusion Face recognition technologies have been associated generally with very costly top secure applications. Today the core technologies have evolved and the cost of equipments is going down dramatically due to the intergration and the increasing processing power. Certain applications of face recognition technology are now cost effective, reliable and highly accurate.