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Biometric Image Enhancement, Feature Extraction and Recognition Comprising FFT and Gabor Filtering

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Intelligent Computing (SAI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 858))

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Abstract

Biometrics is a technology used to identify, analyze, and measure an individual’s physical and behavioral characteristics. It is used for authenticating and authorizing a person. Among all other biometric authentication, fingerprint recognition is the most known and used solution to authenticate people on biometric systems. Usually, fingerprint recognition approaches are minutiae-based and correlation-based. However, the minutiae-based approach is popular and extensively used method for fingerprint authentication, it shows poor performance for low quality images and insecure over data-passing channel. In proposed methodology, feature-based approach for fingerprint recognition is developed by enhancing the low quality image using FFT and Gaussian filter and by extracting the feature of the image using Gabor filter. Similarity measurement is done by calculating the cosine-similarity value of correlation factors. The cosine-similarity value of correlation factors of input image and template image are computed and compared. If it is over a certain threshold the result of the matching process is positive otherwise negative.

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Correspondence to Al Bashir .

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Bashir, A., Tabassum, M., Naeem, N. (2019). Biometric Image Enhancement, Feature Extraction and Recognition Comprising FFT and Gabor Filtering. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Computing. SAI 2018. Advances in Intelligent Systems and Computing, vol 858. Springer, Cham. https://doi.org/10.1007/978-3-030-01174-1_44

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