• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.359-361
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• 2008

This paper presents the fuzzy minutiae-based matching to improve the accuracy of the difference between template and imput fingerprint image. Minutiae-based matching method is the most well-known and widely used method for fingerprint matching. However, fingerprint pressure, dryness of the skin, skin disease, sweat, dirt, grease, and humidity in the air cause the noisy fingerprint images and the distortion is produced by users moving their fingers on the scanner surface. The input image may be rejected from the Fingerprint Recognition System, because the distorted fingerprint image is very different from the original image. Large tolerence boxes and fuzzy discriminant function is required to improve the accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1787-1793
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• 2008

Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In this paper, we propose a new data structure, called Union and Division, for processing binarized digital fingerprint image efficiently. We present a minutiae extraction algorithm that is using Union and Division and consists of binarization, noise removal, minutiae extraction stages.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.7-12
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• 2004

This thesis studies about thinning compensation and the removal of pseudo minutiae using ridge trace. As for the process of thinning compensation, first, it removes unnecessary pixel when 8-neighbor connection sum among the pixels with the crossing count number 6 is not 3. Second, it deals with repeatedly until there is no pixel to remove while tracing the ridge, beginning with the pixel equivalent to the ridge and the pixel with the crossing count number 2 among the 8 pixels around the pixels with the crossing count number 6. When the thinning compensation is finished, it extracts substitute minutiae to use the crossing count number and the 8-neighbor connection sum. Among the extracted substitute minutiaes, it extracts the real minutiae to utilize the pseudo minutiae removal algorithm again. It compares with the existing method for the performance evaluation of proposal method. By the experimental results, The proposal method indicated that a degree of thinning is excellent and a lot of minutiaes were removed.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.53-60
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• 2008

Fingerprint verification method based on minutiae has been widely used for its speed and size stemming from utilizing only a few data, but it is vulnerable to some errors caused by the false minutiae extractions. A number of suggestions have been made to correct these problems. However, because it is very difficult to avoid all the external factors, such as noises that occur when fingerprints are collected, and all the internal factors that occur during the process of them, there is a limit in minimizing errors by improving the whole process. On the other hand, a fingerprint verification method based on images yields fewer errors because it makes direct comparison between images not using minutiae. Image-based fingerprint verification method has its limitations in aligning images with accuracy. Therefore, this paper proposes a new methodology to improve the performance utilizing both image-based and minutiae-based verification methods effectively. As the result of experimenting with both images and minutiae, the false accept rate and the false reject rate have been improved from 2.7% to 0.8% and from 6.5% to 5.5%, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.51-64
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• 2004

This paper proposes an algerian of generating a tuner-template from multiple fingerprint impressions using a data fusion technique for fingerprint enrollment. The super-template is considered as a single fingerprint template which contains most likely true minutiae based on multiple fingerprint images. The proposed algorithm creates the super template by utilizing a recursive Bayesian estimation method (RBEM), which assumes a sequential fingerprint input model and estimates the credibility of the minutiae in previous input templates froma current input template. Consequently. the RBEM assigns a higher credibility to commonly detectable minutiae from several input templates and a lower credibility to rarely found minutiae from other input templates. Likewise, the RBEM is able to estimate a credibility of the minutia type (ridge ending or bifurcation). Preliminary experiments demonstrate that, as the number of fingerfrint images increases, the performance of recognition can be improved while maintaining the processing time and the size of memory storage for tile super-template almost constant.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.203-211
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• 2005

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 Korea Multimedia Society
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• v.8 no.6
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• pp.761-767
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• 2005

The personal identification procedure through the fingerprints is divided as the classification process by the type of the fingerprints and the matching process to confirm oneself. Many existing researches for the classification and the matching of the fingerprint depend on the number of the minutiae of the fingerprints and the flow patterns by their direction information. In this paper, we focus on extracting the singular points by using the flow patterns of the direction information from identification. The extracted singular points are utilized as a standard point for the matching process by connecting with the extracted information from the singular point embodied. The orthogonal coordinates which is generated by the axises of the standard point can increase the accuracy of the fingerprints matching because of minimizing the effects on the location changes of the fingerprint images.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1327-1342
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• 2010

With the wide deployment of biometric authentication systems, several issues pertaining security and privacy of the biometric template have gained great attention from the research community. To resolve these issues, a number of biometric template protection methods have been proposed. However, the design of a template protection method to satisfy four criteria, namely diversity, revocability and non-invertibility is still a challenging task, especially performance degradation when template protection method is employed. In this paper, we propose a novel method to generate a revocable minutiae-based fingerprint template. The proposed method consists of feature extraction from fingerprint minutiae pairs, quantization, histogram binning, binarization and eventually binary bit-string generation. The contributions of our method are two fold: alignment-free and good performance. Various experiments on FVC2004 DB1 demonstrated the effectiveness of the proposed methods.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.421-436
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• 2012

Different types of fingerprint detection algorithms that are based on extraction of minutiae points are prevalent in recent literature. In this paper, we propose a new algorithm to locate the virtual core point/centroid of an image. The Euclidean distance between the virtual core point and the minutiae points is taken as a random variable. The mean, variance, skewness, and kurtosis of the random variable are taken as the statistical parameters of the image to observe the similarities or dissimilarities among fingerprints from the same or different persons. Finally, we verified our observations with a moment parameter-based analysis of some previous works.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1027-1036
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• 2012

Among various biometrics recognition systems, statistical fingerprint recognition matching methods are considered using minutiae on fingerprints. We define similarity distance measures based on the coordinate and angle of the minutiae, and suggest a fingerprint recognition model following statistical distributions. We could obtain confidence intervals of similarity distance for the same and different persons, and optimal thresholds to minimize two kinds of error rates for distance distributions. It is found that the two confidence intervals of the same and different persons are not overlapped and that the optimal threshold locates between two confidence intervals. Hence an alternative statistical matching method can be suggested by using nonoverlapped confidence intervals and optimal thresholds obtained from the distributions of similarity distances.