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Wavelet Scalar Quantization


Affiliations
1 Department of Electronics and Communication Engineering, Government Polytechnic, Proddatur, India
2 J.N.T.University, Kakinada, A.P, India
 

Fingerprints are today the most widely used biometric features for personal identification. With the increasing usage of biometric systems the question arises naturally how to store and handle the acquired sensor data. Our algorithm for the digitized images is based on adaptive uniform scalar quantization of discrete wavelet transform sub band decomposition. This technique referred to as the wavelet scalar quantization method. The algorithm produces archival quality images at compression ratios of around 15 to 1 and will allow the current database of paper finger print cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.

Keywords

Fingerprint Compression, Discrete Wavelet, Binarization, Adaptive Quantization.
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  • Wavelet Scalar Quantization

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Authors

B. Karuna Kumar
Department of Electronics and Communication Engineering, Government Polytechnic, Proddatur, India
K. Satya Prasad
J.N.T.University, Kakinada, A.P, India

Abstract


Fingerprints are today the most widely used biometric features for personal identification. With the increasing usage of biometric systems the question arises naturally how to store and handle the acquired sensor data. Our algorithm for the digitized images is based on adaptive uniform scalar quantization of discrete wavelet transform sub band decomposition. This technique referred to as the wavelet scalar quantization method. The algorithm produces archival quality images at compression ratios of around 15 to 1 and will allow the current database of paper finger print cards to be replaced by digital imagery. A compliance testing program is also being implemented to ensure high standards of image quality and interchangeability of data between different implementations.

Keywords


Fingerprint Compression, Discrete Wavelet, Binarization, Adaptive Quantization.