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You are here:Open notes-->Seminar-topics-and-ppt-for-engineering-->face-recognition-technology

face recognition technology

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The face is an important part of who you are and how people identify you. Except in the case of identical twins, the face is arguably a person's most unique physical characteristics. While humans have the innate ability to recognize and distinguish different faces for millions of years , computers are just now catching up.

For face recognition there are two types of comparisons .the first is verification. This is where the system compares the given individual with who that individual says they are and gives a yes or no decision. The second is identification. This is where the system compares the given individual to all the

other individuals in the database and gives a ranked list of matches. All identification or authentication technologies operate using the following four stages:

• Capture: a physical or behavioral sample is captured by the system during enrollment and also in identification or verification process.
• Extraction: unique data is extracted from the sample and a template is created.
• Comparison: the template is then compared with a new sample.
• Match/non match : the system decides if the features extracted from the new sample are a match or a non match.

Face recognition technology analyze the unique shape ,pattern and positioning of the facial features. Face recognition is very complex technology and is largely software based. This Biometric Methodology establishes the analysis framework with tailored algorithms for each type of biometric device. Face recognition starts with a picture, attempting to find a person in the image. This can be accomplished using several methods including movement, skin tones, or blurred human shapes. The face recognition system locates the head and finally the eyes of the individual. A matrix is then developed based on the characteristics of the individual’s face. The method of defining the matrix varies according to the algorithm (the mathematical process used by the computer to perform the comparison). This matrix is then compared to matrices that are in a database and a similarity score is generated for each comparison.

Artificial intelligence is used to simulate human interpretation of faces. In order to increase the accuracy and adaptability , some kind of machine learning has to be implemented.

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