• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.297-300
• /
• 2003

In this paper, fingerprint minutiae mosaicking algorithm using minutiae of fingerprint is proposed. First, minutiae map is generated from minutiae of fingerprint and minutiae constellation is generated from fingerprint minutiae map. Minutiae constellation is constellation-shaped structure generated from Voronoi Diagram and Delaunay Triangulation using information of minutiae. Secondly, common region is detected by similarity of minutiae constellation of fingerprint minutiae map and minutiae map of individual fingerprint image is composed. Consequently composite minutiae map by mosaicking of fingerprint minutiae improve the performance of the fingerprint matching system.

• KSCI Review
• /
• v.14 no.1
• /
• pp.265-271
• /
• 2006

In this paper, we propose a new automatic fingerprint identification system that identifies individuals in large databases. The algorithm consists of three steps: preprocessing, classification, and matching, in the classification, we present a new classification technique based on the statistical approach for directional image distribution. In matching, we also describe improved minutiae candidate pair extraction algorithm that is faster and more accurate than existing algorithm. In matching stage, we extract fingerprint minutiaes from its thinned image for accuracy, and introduce matching process using minutiae linking information. Introduction of linking information into the minutiae matching process is a simple but accurate way, which solves the problem of reference minutiae pair selection in comparison stage of two fingerprints quickly. This algorithm is invariant to translation and rotation of fingerprint. The proposed system was tested on 1000 fingerprint images from the semiconductor chip style scanner. Experimental results reveal false acceptance rate is decreased and genuine acceptance rate is increased than existing method.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.37 no.3
• /
• pp.12-26
• /
• 2000

In this paper, we propose a post-processing algorithm to remove false minutiae which decrease the overall performance of an automatic fingerprint identification system by increasing computational complexity, FAR(False Acceptance Rate), and FRR(False Rejection Rate) in matching process. The proposed algorithm extracts candidate minutiae from thinned fingerprint image. Considering characteristics of the thinned fingerprint image, the algorithm selects the minutiae that may be false and located in recoverable area. If the area where the selected minutiae reside is thinned incorrectly due to noise and loss of information, the algorithm recovers the area and the selected minutiae are removed from the candidate minutiae list. By examining the ridge pattern of the block where the candidate minutiae are found, true minutiae are recovered and in contrast, false minutiae are filtered out. In an experiment, Fingerprint images from NIST special database 14 are tested and the result shows that the proposed algorithm reduces the false minutiae extraction rate remarkably and increases the overall performance of an automatic fingerprint identification system.

• IEIE Transactions on Smart Processing and Computing
• /
• v.5 no.1
• /
• pp.43-48
• /
• 2016

We propose plain fingerprint classification based on a core stochastic algorithm that effectively uses a core stochastic model, acquiring more fingerprint minutiae and direction, in order to increase matching performance. The proposed core stochastic algorithm uses core presence/absence and contains a ridge direction and distribution map. Simulations show that the fingerprint classification accuracy is improved by more than 14%, on average, compared to other algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.3
• /
• pp.93-100
• /
• 2004

This paper presents a method to integrate the multiple impressions of a finger for improving fingerprint verification performance. Small-sized sensor has advantage that it can be used in many application fields. However, sufficiently large impression of fingerprint is not available due to the small sensing area, and this degrades the verification performance of the system. The proposed method overcomes this problem by combining the information of fingerprints for enrollment. To combine the fingerprints, the alignment process is important first of all. In the proposed algorithm multiple impressions of a finger are coarsely aligned using the corresponding minutiae pairs and then are finely aligned using the Distance Map. We construct an integrated template for enrollment in aligned coordinate system Since this integrated template represents the enlarged finger region, the problem that is occurred by using small sensor can be overcome. Experimental results show that the use of the integrated template of multiple impressions improves the performance of the fingerprint verification system.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.45 no.5
• /
• pp.110-116
• /
• 2008

This paper presents a new postprocessing method to eliminate the false minutiae, that caused by the skelectonization of fingerprint image, and an image compression method using Isometric Self Organizing Map(ISOSOM). Since the SOM has simple structure, fast encoding time, and relatively good classification characteristics, many image processing areas adopt this such as image compression and pattern classification, etc. But, the SOM shows limited performances in pattern classification because of it's single layer structure. To maximize the performance of the pattern classification with small code book, we a lied the Isometric SOM with the isometry of the fractal theory. The proposed Isometric SOM postprocessing and compression algorithm of fingerprint image showed good performances in the elimination of false minutiae and the image compression simultaneously.