• 한국통신학회논문지
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• 제28권9C호
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• pp.860-867
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• 2003

본 논문에서는 방향 패턴 레이블링을 이용하여 지문 영상의 중심점을 검출하는 방법을 제안하였다. 중심점은 지문영상에서의 특이점들 중의 하나이며 대부분의 지문 인식 시스템에서 기준점으로 사용되고 있다. 중심점의 검출은 지문 인식 시스템에서 반드시 수행되어야할 중요한 단계로 전체 시스템의 성능에 큰 영향을 준다. 제안된 방법에서는 ridge의 분포로부터 얻어낸 방향 성분에 레이블링 방법과 중심점의 위치를 결정하는 알고리즘을 적용하여 중심점의 위치를 검출할 수 있었다. 모의 실험 결과 제안한 방법이 Poincare index와 Sine map 방법들에 비해 수행시간과 검출률 모두에서 좀더 나은 성능을 보임을 확인하였다. 특히 제안한 방법은 arch 형의 중심점 검출에 있어 Poincare index 방법의 낮은 검출률과 Sine map 방법의 긴 수행 시간이라는 단점들을 모두 극복하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.238-241
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• 2000

A fingerprint core-point detection algorithm is presented in this paper. Core-point is useful for fingerprint classification and also for the fingerprint verification since it giver a reference to a fingerprint. Traditional methods of finding the core-point is introduced. These methods are the method using poincare index and the method using sine component of ridge directions. The proposed method is modified algorithm of the latter using the poincare index. The experimental results show that the proposed algorithm achieves almost the same accuracy with faster speed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.429-432
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• 2001

지문영상의 특이점(Singularities) 중의 하나인 Core Point는 대부분의 지문인증 시스템에서 기준점(Reference Point)으로 사용되고 있다. 또한 Core Point의 검출은 전체 지문인증 시스템의 가장 기본적인 단계로서 전체 시스템의 성능에 많은 영향을 준다. 본 논문에서는 지문 영상의 방향 패턴(Orientation Pattern)과 이의 리레이블링(Re-labeling)을 이용한 Core Point 검출 방법을 제안하고, 기존의 Poincare Index를 이용하는 방법 및 Sine Map을 이응한 방법과 비교, 분석하였다.

• 동력기계공학회지
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• 제19권3호
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• pp.11-15
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• 2015

In this paper, the multi-point hydrogen detection system based on the combination of the hetero-core optical fiber SPR hydrogen tip sensor and interrogator by pseudorandom noise (PN) code correlation reflectometry has been developed. In a light intensity-based experiment with an LED operating at 850 nm, it has been presented that a transmitted loss change of 0.32dB was induced with a response time of 25 s for 4% $H_2$ in $N_2$ in the case of the 25-nm Au, 60-nm $Ta_2O_5$, and 5-nm Pd multi-layers film. The proposed sensor characteristic shows excellent reproducibility in terms of loss level and time response for the in- and out- $H_2$ action. In addition, in the experiment for multi-point hydrogen detection, all sensors show the real-time response for 4% hydrogen adding with reproducible working. As a result, the real-time multi-point hydrogen detection could be realized by means of the combination of interrogating system and hetero-core optical fiber SPR hydrogen tip sensors.

• 전기학회논문지
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• 제56권7호
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• pp.1321-1323
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• 2007

A new reference point location method based on an edge map is proposed, where an orientation map is defined and used to find the edge map. Experimental results show that the proposed method can effectively detect the core point in poor quality and arch-type fingerprint images and produces better results in terms of the detection rate and accuracy than the sine map-based method.

• Journal of Information Processing Systems
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• 제8권3호
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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.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2004년도 추계학술발표논문집(상)
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• pp.821-824
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• 2004

본 논문은 지문인식률에 있어서 중요한 요소인 중심점(core point) 검출에 대하여 기존의 Poincare 지수를 이용하는 방법과 Sine을 취하는 방법의 결점을 해결하기 위해 마스크 블록을 이용하여 중심점을 검출 하는 방법을 제안하였다. 이에 대한 실험결과는 기존의 방법보다 빠르면서 검출 일관성에서도 좀더 나은 결과를 나타내었고 Arch형 지문의 중심점 검출에 있어서도 기존 방법들의 오류를 줄일 수 있었다.

• 동력기계공학회지
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• 제16권6호
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• pp.86-91
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• 2012

A multi purpose environmental monitoring system has been developed as a commercially available standard using the techniques which are FBG(Fiber Bragg Grating), Hetero-core spliced fiber optic sensor and etc, for the purposes of monitoring large scaled structures and preserving natural environments. The monitoring system has been tested and evaluated in a possible outdoor condition in view of the full scaled operation at actual sites to be monitored. Additionally, the developed systems in the previous works conveniently provided us with various options of sensor modules intended for monitoring such physical quantities as displacement, distortion, pressure, binary states, and liquid adhesion. In this paper, we extend the previous results to a water leakage detection problem and develop a sensing system as a result. By the experimental study, it is verified that multi-point leakage detection is possible using single line optical fiber.

• Journal of Information Processing Systems
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• 제12권1호
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• pp.83-99
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• 2016

The latest research on the image-based fingerprint matching approaches indicates that they are less complex than the minutiae-based approaches when it comes to dealing with low quality images. Most of the approaches in the literature are not robust to fingerprint rotation and translation. In this paper, we develop a robust fingerprint matching system by extracting the circular region of interest (ROI) of a radius of 50 pixels centered at the core point. Maximizing their orientation correlation aligns two fingerprints that are to be matched. The modified Euclidean distance computed between the extracted orientation features of the sample and query images is used for matching. Extensive experiments were conducted over four benchmark fingerprint datasets of FVC2002 and two other proprietary databases of RFVC 2002 and the AITDB. The experimental results show the superiority of our proposed method over the well-known image-based approaches in the literature.

• 스마트미디어저널
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• 제11권7호
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• pp.94-103
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• 2022

Weeds bring disadvantages to crops since they can damage them, and a clean treatment with less pollution and contamination should be developed. Artificial intelligence gives new hope to agriculture to achieve smart farming. This study delivers an automated weeds growth point detection using deep learning. This study proposes a combination of semantic graphics for generating data annotation and U-Net with pre-trained deep learning as a backbone for locating the growth point of the weeds on the given field scene. The dataset was collected from an actual field. We measured the intersection over union, f1-score, precision, and recall to evaluate our method. Moreover, Mobilenet V2 was chosen as the backbone and compared with Resnet 34. The results showed that the proposed method was accurate enough to detect the growth point and handle the brightness variation. The best performance was achieved by Mobilenet V2 as a backbone with IoU 96.81%, precision 97.77%, recall 98.97%, and f1-score 97.30%.