• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.57-64
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• 2009

In this paper, We propose an highly efficient preprocessing technique for improving the performance of the crease extraction method, which can improve the accuracy of feature extraction within the fingerprint image. The proposed method applies the 1-dimensional directional slit for each pixel in fingerprint image. Once the direction of every pixel in crease candidate area is estimated, it is decomposed into different images depending on their direction. From the directional images, the crease clusters are estimated by utilizing the property of crease area. The proposed method finally extracts the crease from the crease clusters estimated from directional images.

• 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.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• ETRI Journal
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• v.31 no.5
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• pp.628-630
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• 2009

Recently, Ratha and others proposed a cancelable biometrics scheme which transforms an original fingerprint template into a new one using a noninvertible transformation. However, we show that the original template is recovered by a dictionary attack if two transformed templates originating from it are revealed. In our attack, we simulate the transformation and construct a set of possible pre-images for each transformed template. Then, we find the correct pre-image by computing the intersection of these sets. We present an algorithm implementing this idea as well as successful experimental results.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.721-724
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• 2000

This paper presents fingerprint authentication method based on minutiae quadrangle definded by neighboring two Delaunay triangles. In this method, we first make minutiae triangle through Delaunay triangulation which adaptively connect neighboring minutiae according to the local minutiae density distribution, and then use feature vectors in authentication which is extracted from the minutiae quadrangle formed by neighboring two minutiae triangles. This prevents the degradation of matching ratio caused by the errors in image processing or local deformation of the fingerprint, and we can authenticate more discriminately as this method reflects wider local area's topological features than the features extracted from the individual minutiae triangles. To evaluate the proposed algorithm's performance, experiment are conducted on 120 fingerprints, of which size is 256 ${\times}$ 364 with 500dpi resolution. Robust authentications are possible with low FRR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.7
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• pp.1113-1119
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• 2002

In this paper, it was presented that broadly delivered scanner devices can also used in finger print recognition process and then modified existing steps of fingerprint image Processing. First, using the adaptive binary method, that effect was certified already, increased the effect of the results. And then, applying table mapping methods that looks for elements from look-up table, decreased the processing time, too. Finally, it was presented that ridge-direction characteristics extracted from these processes can used effectively In the area of fingerprint recognition system.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.449-450
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• 2006

This paper describes an adaptive hybrid fingerprint matching method using minutiae, filterbank, and the quality of fingerprint. We estimate the quality of each block in the fingerprint image and extract the probability expectation about the quality of each block. By using this expectation, we could achieve the robust matching rate despite of noise distortion. The matching rate of the proposed method is higher than that of other methods. However, the matching speed is similar with that of others as shown in the results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.386-390
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• 2002

In this paper, it was presented that broadly delivered scanner devices can also used in finger print recognition process and then modified existing steps of fingerprint image processing. First, using the adaptive binary method, that effect was certified already, increased the effect of the results. And then, applying table mapping methods that looks for elements from look-up table, decreased the processing time, too. Finally, it was presented that ridge-direction characteristics extracted from these processes can used effectively in the area of fingerprint recognition system.

• 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).

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