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Fingerprint Indexing Based on Novel Features of Minutiae Triplets
May 2003 (vol. 25 no. 5)
pp. 616-622
Bir Bhanu, IEEE
Xuejun Tan, IEEE

Abstract—This paper is concerned with accurate and efficient indexing of fingerprint images. We present a model-based approach, which efficiently retrieves correct hypotheses using novel features of triangles formed by the triplets of minutiae as the basic representation unit. The triangle features that we use are its angles, handedness, type, direction, and maximum side. Geometric constraints based on other characteristics of minutiae are used to eliminate false correspondences. Experimental results on live-scan fingerprint images of varying quality and NIST special database 4 (NIST-4) show that our indexing approach efficiently narrows down the number of candidate hypotheses in the presence of translation, rotation, scale, shear, occlusion, and clutter. We also perform scientific experiments to compare the performance of our approach with another prominent indexing approach and show that the performance of our approach is better for both the live scan database and the ink based database NIST-4.

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Index Terms:
Fingerprint identification, indexing performance, NIST-4 database, triangle features.
Citation:
Bir Bhanu, Xuejun Tan, "Fingerprint Indexing Based on Novel Features of Minutiae Triplets," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 25, no. 5, pp. 616-622, May 2003, doi:10.1109/TPAMI.2003.1195995
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