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Fingerprint Enhancement Based on Ridge Orientation and Ridge Frequency


Affiliations
1 Department of Computer Science, Avinashilingam University for Women, Coimbatore-641043, Tamilnadu, India
2 Computer Centre, Avinashilingam, University for Women, Coimbatore-641043, Tamilnadu, India
3 Computer Centre, Avinashilingam University for Women, Coimbatore-641043, Tamilnadu, India
     

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The performance of any fingerprint recognizer highly depends on the fingerprint image quality. Different types of noises in the fingerprint images pose greater difficulty for recognizers. Most Automatic Fingerprint Identification Systems (AFIS) use some form of image enhancement. Although several methods have been described in the literature, there is still scope for improvement. In order to ensure that the performance of an automatic fingerprint identification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. This paper presents a fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency.

Keywords

Fingerprint Enhancement, Minutiae Extraction, Ridge, Valley, Ridge Orientation, Ridge Frequency, AFIS.
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  • Fingerprint Enhancement Based on Ridge Orientation and Ridge Frequency

Abstract Views: 160  |  PDF Views: 2

Authors

S. Malathi
Department of Computer Science, Avinashilingam University for Women, Coimbatore-641043, Tamilnadu, India
S. Umamaheswari
Computer Centre, Avinashilingam, University for Women, Coimbatore-641043, Tamilnadu, India
C. Meena
Computer Centre, Avinashilingam University for Women, Coimbatore-641043, Tamilnadu, India

Abstract


The performance of any fingerprint recognizer highly depends on the fingerprint image quality. Different types of noises in the fingerprint images pose greater difficulty for recognizers. Most Automatic Fingerprint Identification Systems (AFIS) use some form of image enhancement. Although several methods have been described in the literature, there is still scope for improvement. In order to ensure that the performance of an automatic fingerprint identification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. This paper presents a fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency.

Keywords


Fingerprint Enhancement, Minutiae Extraction, Ridge, Valley, Ridge Orientation, Ridge Frequency, AFIS.