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Low Quality Fingerprint Template Encryption Algorithm

Low Quality Fingerprint Template Encryption Algorithm

Amjad Ali1, Muhammad Amir2*, Bilal Ur Rehman2, Zafar Khan3 and Abid Munir1
 

 
1Department of Electrical Engineering, UET, Jalozai Campus, Khyber Pakhtunkhwa, Peshawar, Pakistan; 2Department of Electrical Engineering, UET, Khyber Pakhtunkhwa, Peshawar, Pakistan; 3Faculty of Engineering and IT, Northern University, Nowshera, Khyber Pakhtunkhwa, Pakistan.

*Correspondence: Muhammad Amir, Department of Electrical Engineering, UET, Khyber Pakhtunkhwa, Peshawar, Pakistan; Email: [email protected] 

ABSTRACT

Nowadays,biometric data protection is one of the main security parameters to be looked after. In fingerprint processing, initially, appropriate proven methods are used for processing fingerprints in a sequential manner followed by the application of various encryption algorithms for ensuring protection of such biometric data. In fingerprinting, image processing techniques include: low-quality-fingerprint enhancement, normalization, binarization and thinning of fingerprint image followed by feature extraction. In this paper, a novel encryption method for minutiae based low-quality-fingerprint framework is proposed. The proposed encryption algorithm works through addition of spurious information to the originally extracted fingerprint data. The addition of spurious information is in correlation with the originally extracted features. The proposed approach is best suited for minutiae based information encryption and the proposed encryption algorithm has been tested using the standard fingerprint verification competition database (FVC-DB1-2002). The image processing techniques, the proposed encryption technique and the results were processed using MATLAB. The empirical results presented in this paper demonstrate an overall improvement through the proposed approach as the similarity standards are almost distinct. Moreover, results of the proposed technique exhibit the weakest of correlations between the original and encrypted data during extraction of low quality fingerprints thus enhancing verification and data protection. 

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Journal of Engineering and Applied Sciences

December

Vol. 42, pp. 01-48

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