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Efficient 2‐fold contextual filtering approach for fingerprint enhancement

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Automated personal authentication has become increasingly important in modern information driven society and in this regard fingerprint‐based personal identification is considered to be the most effective tool. In order to ensure reliable fingerprint identification and improve fingerprint ridge structure, a novel fingerprint enhancement approach is presented based on local adaptive contextual filtering. The proposed enhancement technique is 2‐fold as it involves processing both in frequency and spatial domain. The fingerprint image is first filtered in frequency domain and then local directional filtering in spatial domain is applied to obtain enhanced fingerprint. In order to determine the performance efficiency of the proposed enhancement technique, a comparative analysis of error rates on standard fingerprint databases has been presented with major contextual enhancement schemes. The results show the efficacy of the proposed scheme as compared with other contextual filtering techniques.
Title: Efficient 2‐fold contextual filtering approach for fingerprint enhancement
Description:
Automated personal authentication has become increasingly important in modern information driven society and in this regard fingerprint‐based personal identification is considered to be the most effective tool.
In order to ensure reliable fingerprint identification and improve fingerprint ridge structure, a novel fingerprint enhancement approach is presented based on local adaptive contextual filtering.
The proposed enhancement technique is 2‐fold as it involves processing both in frequency and spatial domain.
The fingerprint image is first filtered in frequency domain and then local directional filtering in spatial domain is applied to obtain enhanced fingerprint.
In order to determine the performance efficiency of the proposed enhancement technique, a comparative analysis of error rates on standard fingerprint databases has been presented with major contextual enhancement schemes.
The results show the efficacy of the proposed scheme as compared with other contextual filtering techniques.

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