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Published byStuart Logan Modified over 8 years ago
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Access Control Via Face Recognition
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Group Members Thilanka Priyankara Vimalaharan Paskarasundaram Manosha Silva Dinusha Perera
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Introduction What is Recognition ? Can you recognize this guy? Face is belonged to the different guy. You will feel because your brain is trained to track such things.
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Who is this?
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Types of Access Control Recognition Finger Print Shape of Ear Retina Recognition Face Recognition
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Advantages of Facial Recognition Give more percentage of guaranty compared to other techniques. Intruders should take more effort to get into the system. (Making a Mask) With another mechanism, system can be made to more secure
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What we are going to do? Access Control System 2 way access mechanism 1.Bar code 2.Face Recognition If both mechanisms are satisfied only user can enter the implemented area
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Facial Recognition We use 1.Computer Vision 2.Neural Networks 3.??????????????
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Without Neural Network If straight forward matching is used Noise can be there and different lighting If user comes with a moustache which he didn’t have before 2 weeks will not be allowed to get in Ooh should I have shave my moustache to get in??
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Why Neural Network? Adaptive-learning When users training the system it will keep on learning about the domain. Self-organization It gathers the knowledge and organize it by itself Fault-tolerance capabilities It can tolerate the noise small variations These features are very much needed to do a system which can do the human like recognizing
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Techniques Face recognition uses mainly the following techniques: Facial geometry: uses geometrical characteristics of the face. May use several cameras to get better accuracy (2D, 3D...) Skin pattern recognition (Visual Skin Print) Facial thermogram: uses an infrared camera to map the face temperatures Smile: recognition of the wrinkle changes when smiling
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Facial Geometry When searching for the facial features in the face image, Look for high level features first E.g. eyes, nose, mouth Then relative to high level features look at the positions of low level features E.g. eyebrows
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Problems faced, Identifying a Face find the face in the image Face finding solves the important task of making face recognition translation Scaling of the face image Distance from the camera Rotation of the face image if needed Lighting conditions at the time the picture is taken
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Conclusion Not easy Neural network training will eat the time
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Conclusion cont… Core technologies are highly researched Facial scan has unique advantages over other biometrics Automated facial detection and facial recognition algorithm are not yet mature Facial-recognition systems create opportunities to identify people unobtrusively
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