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Capturing data can be done in various ways; the best method depends on application. In biometric security systems, capture is the acquisition of or the process of acquiring and identifying characteristics such as finger image, palm image, facial image, iris print, or voiceprint which involves audio data, and the rest all involve video data.
Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.
Iris recognition is widely applied by organisations dealing with the masses, one being the Aadhaar identification carried out by the Government of India to keep records of its population. The reason for this is that iris recognition makes use of iris prints of humans, which hardly evolve during one's lifetime and are extremely stable.
Some of the proposed techniques operate using their own recognition engines, such as Teoh et al. [61] and Savvides et al., [62] whereas other methods, such as Dabbah et al., [63] take the advantage of the advancement of the well-established biometric research for their recognition front-end to conduct recognition. Although this increases the ...
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Face detection is gaining the interest of marketers. A webcam can be integrated into a television and detect any face that walks by. The system then calculates the race, gender, and age range of the face. Once the information is collected, a series of advertisements can be played that is specific toward the detected race/gender/age.
The input is an RGB image of the face, scaled to resolution , and the output is a real vector of dimension 4096, being the feature vector of the face image. In the 2014 paper, [ 13 ] an additional fully connected layer is added at the end to classify the face image into one of 4030 possible persons that the network had seen during training time.
Eigenface provides an easy and cheap way to realize face recognition in that: Its training process is completely automatic and easy to code. Eigenface adequately reduces statistical complexity in face image representation. Once eigenfaces of a database are calculated, face recognition can be achieved in real time.