30-07-2012, 12:22 PM
FACE RECOGNITION USING NEURAL NETWORKS
FACE RECGNITION USING NEURAL NETORKS.pptx (Size: 579.24 KB / Downloads: 29)
BIOMETRICS
Biometrics is the science and technology of measuring and analyzing biological data.
In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements, for authentication purposes.
BACK PROPAGATION
Learning process.
Requires pairs of input and target vectors.
The output vector ‘o ‘is compared with target vector ‘t’.
In case of difference of ‘o’ and ‘t’ vectors, the weights are adjusted to minimize the difference.
CONCLUSION
Face recognition using Eigen faces has been shown to be accurate and fast. When BPNN technique is combined with PCA non linear face images can be recognized easily. Hence it is concluded that this method has the Acceptance ratio is more than 90 % and execution time of only few seconds.
FACE RECGNITION USING NEURAL NETORKS.pptx (Size: 579.24 KB / Downloads: 29)
BIOMETRICS
Biometrics is the science and technology of measuring and analyzing biological data.
In information technology, biometrics refers to technologies that measure and analyze human body characteristics, such as DNA, fingerprints, eye retinas and irises, voice patterns, facial patterns and hand measurements, for authentication purposes.
BACK PROPAGATION
Learning process.
Requires pairs of input and target vectors.
The output vector ‘o ‘is compared with target vector ‘t’.
In case of difference of ‘o’ and ‘t’ vectors, the weights are adjusted to minimize the difference.
CONCLUSION
Face recognition using Eigen faces has been shown to be accurate and fast. When BPNN technique is combined with PCA non linear face images can be recognized easily. Hence it is concluded that this method has the Acceptance ratio is more than 90 % and execution time of only few seconds.