• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.547-559
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• 2010

Delaunay triangulation is suitable for fingerprint matching because of its robustness to rotation and translation. However, missing and spurious minutiae degrade the performance and computational efficiency. In this paper, we propose a method of combining local quality assessment and 4-category minutiae classification to improve accuracy and decrease computational complexity in matching process. Experimental results suggest that removing low quality areas from matching candidate areas and classifying minutiae improve computational efficiency without degrading performance. The results proved that the proposed algorithm outperforms the matching algorithm (BOZORTH3) provided by NIST.

• Journal of KIISE:Software and Applications
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• v.28 no.10
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• pp.764-772
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• 2001

This paper describes fingerprint matching algorithm using connected information between minutiae. We regard minutiae as ridge bifurcation and ridge ending. Features are composed of minutia's position, type(ridge bifurcation or ridge ending) ridge direction and connected ridge information. While the minutiae are extracted, we store connected in information between minutiae on the same ridge. They are used to find corresponding point pairs. Minutiae are aligned completely by two corresponding point pairs and point pattern matching is achieved by counting the number of overlapping pairs. It is invariable t translation and rotation. We have tested proposed method on the 445 fingerprints from 89 persons. These experimental results show that proposed algorithm improve 33% in speed.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.263-266
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• 2000

We proposes a new fingerprint minutia matching algorithm which matches the fingerprint minutiae by using adaptive distance. In general, fingerprint is deformed by pressure and orientation when a user press his fingerprint to sensor. These nonlinear deformations change the distance between minutiae and reduce verification rate. We define the adaptive distance using ridge frequency. Adaptive distance normalizes the distance between minutiae and compensates for nonlinear deformation. Our algorithm can distinguish two different fingerprints better and is more robust. Experimental results show that the performance of the proposed algorithm is superior to using Euclidean distance.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1867-1870
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• 2003

Since degraded region of input image can cause false minutiae which lead to decrease identification performance, use minutiae belong to only good quality to ensure true minutiae. This paper suggests image quality measuring method with respect to local and global orientation of ridges. In order to verify a suggested method, PDFs of quality indices derived by local and global feature are computed and then, classifying each image block using Bayesian decision theory.

• Proceedings of the IEEK Conference
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• 2001.06d
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• pp.195-198
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• 2001

We proposes a new fingerprint minutia matching algorithm which matches the fingerprint minutiae by using local alignment. In general, fingerprint is deformed by Pressure and orientation when a user presses his fingerprint to the sensor. These nonlinear deformations change the position and the orientation of minutiae which decrease reliability of minutiae. Matching by using global alignment uses one alignment point. But, the problem with this method is that, due to the deformation, matching reliability of a minutia decreases as the distance from the alignment minutia increases. Matching by using local alignment overcomes this problem by considering minutiae which are located in a short distance boundary. Experimental results show that the performance of the proposed algorithm is superior to that of using global alignment.

• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1577-1584
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• 2007

Fingerprint verification is being adopted widely to provide positive identification with a high degree of confidence in all practical areas. This popular usage requires reliable methods for matching of these patterns. To meet the latest expectations, the paper presents a pair wise distance histogram method for fingerprint matching. Here, we introduced a randomized algorithm which exploits pair wise distances between the pairs of minutiae, as a basic feature for match. The method undergoes two steps for completion i.e. first it performs the matching locally then global matching parameters are calculated in second step. The proposed method is robust to common problems that fingerprint matching faces, such as scaling, rotation, translational changes and missing points etc. The paper includes the test of algorithm on various randomly generated minutiae and real fingerprints as well. The results of the tests resemble qualities and utility of method in related field.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.237-238
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• 2007

Fingerprint verification based on minutiae mostly has used because it stores a few data and is good for speed. However personal verification errors are caused by extracted from false minutiae. Therefore, in this paper, we propose a new methodology performing together based on image and minutiae. As the result of performing with image and minutiae, false accept rate and false reject rate are improved.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.305-308
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• 2003

The postprocessing of fingerprint image are widely used to eliminate the false minutiae that caused by skeletonization. This paper presents a new postprocessing algorithm of the skeletonized fingerprint image using SOFM. The proposed postprocessing method showed the good performance for eliminating the spurious minutiae.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.248-255
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• 2003

This paper presents a fingerprint recognition algorithm using cross-correlation function. This algorithm consists of minutiae extraction, minutiae alignment and minutiae matching, where we propose a new minutiae alignment method. In our alignment method, the rotation angle between two fingerprints is obtained by using cross-correlation function of the minutia directions, thereafter the displacement is obtained from the rotated fingerprint. This alignment method is capable of finding rotation angle and displacement of two fingerprints without resorting to exhaustive search. Our fingerprint recognition algorithm has been tested on fingerprint images captured with inkless scanner. The experiment results show that 17.299% false rejection ratio(FRR) at 2.086% false acceptance ratio(FAR).