Dorsal Finger Knuckle Identification using Fuzzy Feature Matching

Kavitha Jaba Malar R, Joseph Raj V


Biometric traits are now highly explored by researchers to identify a person. This paper presents an emerging biometric identifier, namely Dorsal finger knuckle Print (DFKP) for personal identification. A Fuzzy Feature Match based on Triangle Feature Set is applied for the improvement of distortions in finger knuckle prints verification system. This method is applied to get the best match with the original image and demonstrates that the minutiae template of an user may be used to reconstruct finger knuckle print images of CETS student and staff members. The performance of the method is also reported. This paper proposes the concept of fixed fingers and fixed number of triangles in the finger knuckle print. The concept of fixed fingers and fixed number of triangles in the dorsal finger knuckle print improves the performance of the method. The proposed system reduces the complexity of the dorsal finger knuckle print triangularization method. It also improves the accuracy.


Distortion, Dorsal, Matching, Verification.


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