Abstract/concept of fingerprints.
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Answer:
The fingerprint recognition system is considered to most important
biometric system in addition to other biometrics recognition systems. The
fingerprint recognition problem can be fingerprint verification and
fingerprint identification.
Fingerprint verification refers to authenticity of a person by his
fingerprint. The user provides fingerprint together with identity
information. In the verification process template is retrieved based on the
identification provided and matching is performed.
fingerprints based upon the unspecified conditions. In the identification of
fingerprint, the process matches fingerprints with the fingerprint database
for similarity.
A good fingerprint is required for the best verification and
identification tasks. Many approaches are available for fingerprint
verification and identification. One method is based on minutia,
representing the fingerprint by its local features, like terminations and
bifurcations. The other method is based on image processing. In this
method, matching is based on the features of the image.
This research work uses decomposition of fingerprint image by
using wavelet method. The wavelet type used is db-1, and coiflet. The
fingerprint image is decomposed to five levels. In each level of
decomposition, the fingerprint image is split into four parts namely:
approximation matrix, vertical matrix, horizontal matrix and a diagonal
matrix. The subsequent level of decomposition uses an approximation of
the previous level for further decomposition.
Statistical features are calculated at each level of decomposition
using all the 4 coefficient matrices. The statistical features are used as
inputs for training the artificial neural network (ANN) and Fuzzy logic
algorithm.
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The purpose of using ANN in the r
Explanation:
The fingerprint recognition system is considered to most important
biometric system in addition to other biometrics recognition systems. The
fingerprint recognition problem can be fingerprint verification and
fingerprint identification.
Fingerprint verification refers to authenticity of a person by his
fingerprint. The user provides fingerprint together with identity
information. In the verification process template is retrieved based on the
identification provided and matching is performed.
fingerprints based upon the unspecified conditions. In the identification of
fingerprint, the process matches fingerprints with the fingerprint database
for similarity.
A good fingerprint is required for the best verification and
identification tasks. Many approaches are available for fingerprint
verification and identification. One method is based on minutia,
representing the fingerprint by its local features, like terminations and
bifurcations. The other method is based on image processing. In this
method, matching is based on the features of the image.
This research work uses decomposition of fingerprint image by
using wavelet method. The wavelet type used is db-1, and coiflet. The
fingerprint image is decomposed to five levels. In each level of
decomposition, the fingerprint image is split into four parts namely:
approximation matrix, vertical matrix, horizontal matrix and a diagonal
matrix. The subsequent level of decomposition uses an approximation of
the previous level for further decomposition.
Statistical features are calculated at each level of decomposition
using all the 4 coefficient matrices. The statistical features are used as
inputs for training the artificial neural network (ANN) and Fuzzy logic
algorithm.