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1.	Bartunek, Josef Strom, et al. (författare) Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data 2013 Ingår i: IEEE Transactions on Image Processing. - : IEEE. - 1941-0042 .- 1057-7149. ; 22:2, s. 644-656 Tidskriftsartikel (refereegranskat)abstract This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are; preprocessing, global analysis, local analysis and matched filtering. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated towards the NIST developed NBIS software for fingerprint recognition on FVC databases.

Bartunek, Josef Strom, et al. (författare)
Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data
2013
Ingår i: IEEE Transactions on Image Processing. - : IEEE. - 1941-0042 .- 1057-7149. ; 22:2, s. 644-656
Tidskriftsartikel (refereegranskat)abstract
- This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are; preprocessing, global analysis, local analysis and matched filtering. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated towards the NIST developed NBIS software for fingerprint recognition on FVC databases.

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