• 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 CI
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• v.45 no.5
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• pp.110-116
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• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.359-367
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• 2004

The postprocessing to remove false minutia is important because the extraction of true minutia affects the performance as a key factor in fingerprint identification system. In this paper, we propose an efficient postprocessing algorithm for removing false minutia among the extracted candidates in a thinned image. The proposed algorithm removes false minutia in three steps by using various information in the acquired fingerprint image: the structural information of minutia (end point and bifurcation), the inherent characteristics of fingerprint, and the quality of acquired images. Under Intel Celeron processor environment with 248${\times}$292 images acquired by optic device, the experiments showed that the proposed algorithm efficiently removed false minutia while preserving true minutia. Moreover, the proposed algorithm takes 0.0154 second, which is very small compared to the time for preprocessing (0.343 second).

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.334-336
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• 2004

The postprocessing of fingerprint images is widely used in the elimination of the false minutiae caused by skeletonization. This paper presents the images were duplicated by The SOFM. And this Method showed that the good performance of eliminating false minutiae and fast processing.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.65-68
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• 2002

In an automatic fingerprint recognition system, a thinning process after binarization is commonly used. However it gives rise to spurs and holes often causing many spurious minutiae. Thus, more elaborate postprocessing is urgently needed to remove such spurious minutiae. To overcome this problem, we present a method of extracting minutiae based on horizontal and vertical run-length encoding from a binary fingerprint image without thinning process. Experimental results show that the proposed method for extracting minutiae is fairly reliable and fast, when il is compared to other method adopting a thinning process.

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