• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.31-33
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• 2021

In this paper, a dataset was designed and built to improve the accuracy of finger direction detection using an object detection algorithm based on You Only Look Once (YOLO). In order to improve the object detection performance, about 200 finger image data sets were trained, and to confirm that the detection accuracy differs from each other according to the angle of the palm, 50 comparison groups of different angles were configured and tested. As a result of the experiment, it was confirmed that the detection accuracy of palm located in a direction close to 90° is higher than that of other angles.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10c
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• pp.284-286
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• 2000

명명(Naming) 서비스 및 디렉토리(Directory) 서비스는 네트워크에 연결된 사용자 PC, 서버, palm, 인터넷 응용서비스, 네트워크 장치, 자바 객체 등에 표준 이름을 부여하여 관련된 다양한 정보를 논리적으로 접근할 수 있도록 지원하는 서비스이다. JNDI(Java Naming and Directory Interface)는 기업 내에서 사용되는 다양한 명명 서비스와 디렉토리 서비스에 대하여 단일의 인터페이스를 사용하여 관리할 수 있도록 지원한다. 본 논문에서는 그룹통신 시스템인 JACE 시스템을 이용하여 동일한 서비스를 제공하는 분산된 명명 서비스와 디렉토리 서비스가 프로세스 그룹으로 동작될 수 있는 JNDS(Java Naming and Directory System)의 설계에 관하여 기술한다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.394-396
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• 2003

스마트폰에 내장되고 있는 Symbian OS, Windows CE .NET, Palm OS와 같이 멀티태스킹을 기본적으로 지원하면서, 다양한 멀티미디어 데이터 서비스의 지원, IPv4, Bluetooth 와 같은 다양한 네트워킹 기술 지원, 데스크 탑 PC와의 데이터 호환 기능 등이 제공되는 최신의 모바일 운영체제들이 개발되면서 멀티미디어 중심의 이동통신 서비스의 변환을 촉진시키고 있다. 이러한 고성능의 모바일 OS들의 기능으로 인한 위피(WIPI)나 퀄컴사의 브루(Brew)와 같은 무선인터넷플랫폼과의 관계를 제시하고 향후 발전 방향과 구조를 제시하고자 한다.

• Journal of the Optical Society of Korea
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• v.19 no.5
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• pp.467-476
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• 2015

Finger vein recognition, which is a promising biometric method for identity authentication, has attracted significant attention. Considerable research focuses on transmission-type finger vein recognition, but this type of authentication is difficult to implement in mobile consumer devices. Therefore, reflection-type finger vein recognition should be developed. In the reflection-type vein recognition field, the majority of researchers concentrate on palm and palm dorsa patterns, and only a few pay attention to reflection-type finger vein recognition. Thus, this paper presents reflection-type finger vein recognition for biometric application that can be integrated into mobile consumer devices. A database is built to test the proposed algorithm. A novel method of region-of-interest localization for a finger vein image is introduced, and a scheme for effectively extracting finger vein features is proposed. Experiments demonstrate the feasibility of reflection-type finger vein recognition.

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.4
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• pp.514-517
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• 2004

Expeller pressed and solvent extracted palm kernel cake (PKC) were force-fed to male and female Muscovy ducks at 7 weeks of age. The nutrient digestibility, apparent metabolizable energy (AME), true metabolizable energy (TME) and true available amino acid (TAAA) digestibilities were determined. There was no significant (p>0.05) effect of the type of PKC used on crude protein (CP), ether extract (EE), metabolizable energy (ME) and amino acid (AA) digestibilities. However, digestibilities of dry matter (DM) and neutral detergent fibre (NDF) was found to be higher in solvent extracted compared to expeller pressed PKC. The average digestibility of DM, CP, NDF and EE were 43, 58, 39 and 89%, espectively. It was found that the ducks utilized about 47% of the gross energy of PKC. The respective average AMEn and TMEn values of PKC for Muscovy ducks was 1,743 and 1,874 kcal/kg. The overall TAAA of PKC for Muscovy ducks was 65%. The data on the TMEn and digestible AA for PKC obtained from this study provide new information with regard to diet formulation for Muscovy ducks.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.681-684
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• 2021

In this paper, we study image clustering without labeling using machine learning techniques. We proposed an unsupervised machine learning technique to design an image clustering model that automatically categorizes images into groups. Our experiment focused on inception convolutional neural networks (inception V3) with k-mean methods to cluster images. For this, we collect the public datasets containing Food-K5, Flowers, Handwritten Digit, Cats-dogs, and our dataset Rice Germination, and the owner dataset Palm print. Our experiment can expand into three-part; First, format all the images to un-label and move to whole datasets. Second, load dataset into the inception V3 extraction image features and transferred to the k-mean cluster group hold on six classes. Lastly, evaluate modeling accuracy using the confusion matrix base on precision, recall, F1 to analyze. In this our methods, we can get the results as 1) Handwritten Digit (precision = 1.000, recall = 1.000, F1 = 1.00), 2) Food-K5 (precision = 0.975, recall = 0.945, F1 = 0.96), 3) Palm print (precision = 1.000, recall = 0.999, F1 = 1.00), 4) Cats-dogs (precision = 0.997, recall = 0.475, F1 = 0.64), 5) Flowers (precision = 0.610, recall = 0.982, F1 = 0.75), and our dataset 6) Rice Germination (precision = 0.997, recall = 0.943, F1 = 0.97). Our experiment showed that modeling could get an accuracy rate of 0.8908; the outcomes state that the proposed model is strongest enough to differentiate the different images and classify them into clusters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.179-182
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• 2010

본 논문에서는 영상으로부터 손금을 추출하기 위해서 획득된 영상을 YCbCr 컬러 공간으로 변환한다. YCbCr 컬러 공간에서 Y:65~255, Cb:25~255, Cr:130~255에 해당되는 피부색 정보를 추출하고 이 피부색 정보를 임계치로 설정하여 손 영역을 추출한다. 추출된 손 영역에서 내부 픽셀의 3:1 이상, 전체 영상의 2:1 이상인 손의 형태학적 정보와 8 방향 윤곽선 추적 기법을 이용하여 잡음을 제거한다. 잡음이 제거된 영상에서 손금을 추출하기 위해서 스트레칭 기법과 소벨 마스크를 이용하여 에지를 추출한다. 추출된 에지 영상에서도 미세한 잡음이 존재하므로 퍼지 이진화 기법을 이용하여 효과적으로 이진화 한다. 이진화된 영상에서 손금의 형태학적 정보를 이용하여 손의 윤곽선을 제외한 손금 영역을 추출한다. 추출된 손금 영역은 동치 테이블을 이용하는 연결 영역 검색 기법과 퍼지 추론 기법을 적용하여 개별 손금의 중요선을 추출하고 분석한다. 다양한 손금 영상을 대상으로 실험한 결과, 제안된 방법이 기존의 손금 추출 방법보다 손금을 분석하는데 효율적인 것을 확인하였다.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.110-112
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• 2003

The researchers, who seek geological and environmental information, depend on the remote sensing and aerial photographic datum from various commercial satellites and aircraft. However, the adverse weather conditions and the expensive equipment can restrict that the researcher can collect their data anywhere and any time. To allow for better flexibility, we have developed a compact, a multispectral automatic Aerial photographic system. This system's Multi-spectral camera can catch the visible (RGB) and infrared (NIR) bands (3032${\ast}$2008 pixel) image. Our system consists of a thermal infrared camera and automatic balance control, and it managed and controlled by a palm-top computer. And it includes a camera gimbals system, GPS receiver, weather sensor and etc. As a result, we have successfully tested its ability to acquire aerial photography, weather data, as well as GPS data, making it a very flexible tool for environmental data monitoring.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.93-96
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• 2022

본 논문에서는 카메라 센서만을 이용하여 손바닥 사진을 촬영하고 추출된 데이터들을 합성하여 멀티 채널 이미지를 생성 및 분류 모델에 입력하여 신원을 확인하는 딥러닝 모델을 제안한다. 이 모델은 손바닥 사진이 입력되면 손바닥 및 손금 세그멘테이션을 이용하여 마스크 이미지를 추출하고 단일 채널로 구성된 이미지들을 멀티 채널 이미지로 합성/재구성하여 신원을 분류하는 딥러닝 모델이다. 이는 카메라 센서 외 다른 센서가 필요 없다는 장점을 가지고 있으며, 비접촉 신원 인식 시스템에 적용할 수 있다.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.131-134
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• 2002

As the increased use of computer, wired/wireless/mobile Internet, security in using Internet becomes a more important problem. Thus, biometric technology using physical and behavior characteristics of a person is hot issue. Many different types of biometric technologies of a person such as fingerprint, face, iris, vein, DNA, brain wave, palm, voice, dynamic signature, etc. had already been studied but remained unsuccessful because they do not meet social demands. However, recently many of these technologies have been actively revived and researchers have developed new products on various commercial fields. Dynamic signature verification technology is to verify the signer by calculating his writing manner, speed, angle, and the number of strokes, order, the down/up/movement of pen when the signer input his signature with an electronic pen for his authentication. Then signature verification system collects mentioned above various feature information and compares it with the original one and simultaneously analyzes to decide whether signature is forgery or true. The prospect of signature verification technology is very promising and its use will be wide spread in terms of economy, security, practicality, stability and convenience.