• Korea Multimedia Society
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• v.7 no.2
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• pp.68-73
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• 2003

• Journal of KIISE:Software and Applications
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• v.32 no.11
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• pp.1136-1146
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• 2005

Fingerprint classification is useful in an automated fingerprint identification system (AFIS) to reduce the matching time by categorizing fingerprints. Based on Henry system that classifies fingerprints into S classes, various techniques such as neural networks and support vector machines (SVMs) have been widely used to classify fingerprints. Especially, SVMs of high classification performance have been actively investigated. Since the SVM is binary classifier, we propose a novel classifier-combination model, multiple decision templates (MuDTs), to classily fingerprints. The method extracts several clusters of different characteristics from samples of a class and constructs a suitable combination model to overcome the restriction of the single model, which may be subject to the ambiguous images. With the experimental results of the proposed on the FingerCodes extracted from NIST Database4 for the five-class and four-class problems, we have achieved a classification accuracy of $90.4\%\;and\;94.9\%\;with\;1.8\%$ rejection, respectively.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.243-251
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• 2008

This study is to suggest the extraction algorithms of fingerprint corepoint and region separation using the labeling for gate security in order that it might be applied to the fingerprint recognition effectively. The gate security technology is entrance control, attendance management, computer security, electronic commerce authentication, information protection and so on. This study is to extract the directional image by dividing the original image in $128{\times}128$ size into the size of $4{\times}4$ pixel. This study is to separate the region of directional smoothing image extracted by each directional by using the labeling, and extract the block that appeared more than three sorts of change in different directions to the corepoint. This researcher is to increase the recognition rate and matching rate by extracting the corepoint through the separation of region by direction using the maximum direction and labeling, not search the zone of feasibility of corepoint or candidate region of corepoint used in the existing method. According to the result of experimenting with 300 fingerprints, the poincare index method is 94.05%, the proposed method is 97.11%.

• 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%.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.249-255
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• 2004

In fingerprint verification and identification, fingerprint and background region should be segmented. For this purpose, most systems obtain variance of brightness of X and Y direction using Sobel mask. To decide given local region is background or not, the variance is compared with a certain threshold. Although this method is simple, most fingerprint image does not separated with two region of fingerprint and background region. In this paper, we presented a new segmentation algorithm based on Run-Length Connectivity analysis. For a given binary image after thresholding, suggested algorithm calculates RL of X and Y direction. Until the given image is segmented to two regions, small run region is successively inverted. Experimental result show that this algorithm effectively separates fingerprint region and background region.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.959-967
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• 2004

Jain et al. proposed the hybrid matching method which was combined the minutia-based matching method and the filter-bank based matching method. And, their experimental results proved the hybrid matching method was more effective than each of them. However, this hybrid method cannot utilize each peculiar advantage of two methods. The reason is that it gets the matching score by simply summing up each weighted matching score after executing two methods individually. In this paper, we propose new hybrid matching method. It mixes two matching methods during the feature extraction process. This new hybrid method has lower ERR than the filter-bank based method and higher ERR than the minutia-based method. So, we propose the adaptive hybrid scoring method, which selects the matching score in order to preserve the characteristics of two matching methods. Using this method, we can get lower ERR than the hybrid matcher by Jain et al. Experimental results indicate that the proposed methods can improve the matching performance up to about 1% in ERR.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.883-886
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• 2003

본 연구에서는 할선법과 모멘트의 고정점 알고리즘 독립성분분석을 이용하여 영상의 특징을 추출하는 기법을 제안하였다. 여기서 할선법은 독립성분 상호간의 정보를 최소화하기 위한 목적함수의 최적화 과정에서 요구되는 1차 미분에 따른 계산을 간략화하기 위함이고, 모멘트는 최적화 과정에서 발생하는 발진을 억제하여 보다 빠른 학습을 위함이다. 제안된 기법을 $256{\times}256$ 픽셀의 10개 지문영상에서 선택된 각각 10,000개의 3가지 영상패치들을 대상으로 적용한 결과, 제안된 기법은 뉴우턴법이나 할선법의 알고리즘 보다도 빠른 특징추출 속도가 있음을 확인하였다 한편 추출된 $16{\times}16$ 펙셀의 160개 독립성분 기저벡터 각각은 영상 각각에 포함된 공간적인 주파수 특성과 방향성을 가지는 경계 특성이 잘 드러나는 국부적인 특징들임을 확인하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.624-631
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• 2002

In this paper, an effective digital watermarking method for copyright protection of binary image data is proposed. First a binary image is grouped into feature regions which has geometrical features and general one. The watermark for authentication is embedded in general regions in order to preserve geometrical features regions. We have used run-length code and special runs for grouping feature regions and general one. For invisibility of watermark, we have embedded the watermark considering transition sensitivity of each pixel in general regions. The proposed method is applied some binary image such as character, signature, seal, and fingerprint image to evaluate performance. By the experimental results, the proposed method preserve feature regions of original image and have higher invisibility of watermarks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.177-180
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• 2002

In this paper, an effective digital watermarking method for copyright protection of binary image data is proposed. First, a binary image is grouped into feature regions which have geometrical features and general one. The watermark for authentication is embedded in general regions in order to preserve geometrical features regions. We have used run-length code and special runs for grouping feature regions and general one. For invisibility of watermark, we have embedded the watermark considering transition sensitivity of each pixel in general regions. The proposed method is applied to some binary image such as character, signature, seal, and fingerprint image to evaluate performance. By the experimental results, the proposed method preserve feature regions of original image and have higher invisibility of watermarks.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.545-551
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• 2003

Henry System which is a traditional fingerprint classification model is difficult to apply to a modem Automatic Fingerprint Identification System (AFIS). To tackle this problem, this study is to apply algorithm for an An Ensemble Fingerprint Classroom System using changes of gradient of ridge in order to improve precise joining speed of a large volume of database. The existing classification system, Henry System, is useful in a captured fingerprint image of core point and delta point using paper and ink. However, the Henry System is unapplicable in modem Automatic Fingerprint Identification System (AFIS) because of problems such as size of input sensor and way of input. This study is to suggest an Ensemble Fingerprint Classroom System which can classify 5 basic patterns of Henry System in uncaptured delta image using changes of gradient of ridge. The proposed fingerprint classification technique will make an improvement of precise joining speed by reducing data volume.