FINGER KNUCKLE-PRINT IDENTIFICATION BASED ON LOCAL AND GLOBAL FEATURE EXTRACTION USING SDOST

Finger knuckle-print biometric system has widely used in modern e-world. The region of interest is needed as the key for the feature extraction in a good biometric system. The symmetric discrete orthonormal stockwell transform provides the computational efficiency and multi-scale information of wave...

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Bibliographic Details
Published in:American journal of applied sciences 2014-06, Vol.11 (6), p.929-938
Main Authors: Kumar, Mahesh N B, Premalatha, K
Format: Article
Language:English
Subjects:
Biometrics
Feature extraction
Fingers
Object recognition
Surface layer
Texture
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Summary:Finger knuckle-print biometric system has widely used in modern e-world. The region of interest is needed as the key for the feature extraction in a good biometric system. The symmetric discrete orthonormal stockwell transform provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods. This motivates researchers to propose a new local and global feature extractor. For the finger knuckle-print, the local and global features are critical for an image observation and recognition. For the finger knuckle-print, the local and global information are critical for an image observation and recognition. The local and global information are physically linked by means of the framework of time frequency analysis. The global feature is exploited to refine the arrangement of finger knuckle-print images in matching. The investigational results indicate that, the proposed work outperforms an existing works with an equal error rate of 0.0045 and 100% correct recognition rate on the finger knuckle-print database.
ISSN:1546-9239
1554-3641
DOI:10.3844/ajassp.2014.929.938