Fingerprint Image Quality Analysis Using TSK Model

Abdelwahed Motwakel Eltayeb

Abstract


The quality of fingerprint image greatly affects the performance of minutiae extraction and the process of matching, thus to analysis fingerprint image quality many research was done. In this paper, we present a novel technique to analysis fingerprint image quality using fuzzy logic on the extracted four features which are the local clarity score (LCS), global clarity score (GCS), ridge_valley thickness ratio (RVTR), and the contrast.  The proposed fuzzy logic system uses Takagi-Sugeno Fuzzy Rule model which can analysis and determinate each fingerprint image type (oily, dry or neutral) based on the extracted feature values and fuzzy inference rules.


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References


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DOI: https://doi.org/10.23956/ijarcsse.v8i7.794

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