• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.90.1-90
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• 2002

Counters for the various kinds of bank notes require high-speed distinctive point extraction and recognition for notes. In this paper we propose a new point extraction and recognition algorithm for bank notes. For distinctive point extraction we use a coordinate data extraction method from specific parts of a bank note representing the same color. The recognition algorithm uses a back-propagation neural network that has coordinate data input. The proposed algorithm is designed to minimize recognition time.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.201-206
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• 2004

Counters for the various kinds of banknotes require high-speed distinctive point extraction and recognition. In this paper we propose a new point extraction and recognition algorithm for Euro banknotes. For distinctive point extraction we use a coordinate data extraction method from specific parts of a banknote representing the same color. To recognize banknotes, we trained 5 neural networks. One is used for inserting direction and the others are used for face value. The algorithm is designed to minimize recognition time by using a minimal amount of recognition data. The simulated results show a high recognition rate and a low training period. The proposed method can be applied to high speed banknote counting machines.

• 전자공학회논문지
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• 제52권6호
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• pp.95-104
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• 2015

최근 모바일 기기의 발전으로 사용자의 위치를 수집하고 분석하는 방법들이 연구되고 있다. 사용자의 특성을 파악하고 궤적 예측 및 패턴을 추출하기 위해 의미 기반 위치 기록을 사용하는 방법이 있다. 의미 기반 위치 기록을 사용하기 위해서는 사용자의 GPS로그를 분석하여 Stay Point를 추출하는 과정이 선행되어야 한다. 기존의 Stay Point 추출 방법은 임의의 중간좌표 즉, 사용자가 실제로 머무르지 않은 지점을 추출하기 때문에 정확하게 사용자가 머무른 위치라고 할 수 없으며, 실내와 실외의 Stay Point를 구분하지 못하는 단점이 있다. 본 논문에서는 이러한 단점을 보완하기 위해 사용자가 실제로 머무른 지점 및 실내에서 머무른 지점만을 추출하는 Stay Point를 제안한다. 기존의 방식으로 추출된 Stay Point에서 가장 가까운 GPS 좌표를 Stay Point로 지정하는 방식(nearSP)과, 사용자가 건물에 들어간 지점을 Stay Point로 지정하는 방식(indoorSP)이다. 제안한 알고리즘은 기존 Stay Point 추출 방법보다 Output 데이터의 용량 감소 및 위치의 정확성이 향상되었고, 실내와 실외를 구분 할 수 있음을 확인할 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.1058-1060
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• 2003

A ground control point (GCP) is a point on the surface of Earth where image coord inates and map coordinates can be identified. The GCP is useful for the geometric correction of systematic and unsystematic errors usually contained in a remotely sensed data. Especially in case of synthetic aperture radar (SAR) data, it has serious geometric distortions caused by inherent side looking geometry. In addition, SAR images are usually severely corrupted by speckle noises so that it is difficult to identify ground control points. We developed a ground point extraction algorithm that has an improved capability. An application of radargrammetry to Daejon area in Korea was studied to acquire the geometric information. For the ground control point extraction algorithm, an ERS SAR data with precise Delft orbit information and rough digital elevation model (DEM) were used. We analyze the accuracy of the results from our algorithm by using digital map and GPS survey data.

• 인터넷정보학회논문지
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• 제6권5호
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• pp.85-95
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• 2005

본 논문에서는 시퀀스 이미지에서 스케일-스페이스 필터링을 통한 특징점 추출과 질감도(texturedness) 비교를 적용한 특징점 추적 알고리즘을 제안한다. 특징점을 추출하기 위해서 정의된 오퍼레이터를 이용하는데, 이때 설정되는 스케일 파라미터는 특징점 선정 및 위치 설정에 영향을 주게 되며, 특징점 추적 알고리즘의 성능과도 관계가 있다. 본 논문에서는 스케일-스페이스 필터링을 통한 특징점 선정 및 위치 설정 방안을 제시한다. 영상 시퀀스에서, 카메라 시점 변화 또는 물체의 움직임은 특징점 추적 윈도우내에 아핀 변환을 가지게 하는데, 대응점 추적을 위한 유사도 측정에 어려움을 준다. 본 논문에서는 Shi-Tomasi-Kanade 추적 알고리즘에 기반하여, 아핀 변환에 비교적 견실한 특징점의 질감도 비교를 수행하는 최적 대응점 탐색 방법을 제안한다.

• 산업기술연구
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• 제22권A호
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• pp.101-105
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• 2002

Counters for various kinds of bank notes require high-speed distinctive point extraction and recognition for notes. In this paper we propose a new point extraction and data extraction method from specific parts of a bank note representing the same color. The recognition algorithm uses a back-propagation neural network that has coordinate data input. The proposed algorithm is designed to minimize recognition time.

• 전자공학회논문지CI
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• 제48권3호
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• pp.46-53
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• 2011

본 논문에서는 대표적인 특징점 추출 알고리즘인 SURF (Speeded Up Robust Features)를 이용한 얼굴 인식 방법을 소개한 다. 일반적으로, SURF를 이용한 물체 인식은 특징점 추출 및 정합만을 수행하지만, 본 논문에서 제안하는 SURF를 이용한 얼굴 인식 방법은 특징점 추출 및 정합뿐만 아니라 얼굴 영상 회전 및 특징점 검증을 추가로 수행한다. 얼굴 영상 회전은 특징점의 수를 증가시키기 위해 수행되며, 특징점 검증은 정확하게 정합된 특징점들을 찾기 위해 수행된다. 비록 본 논문에서 제안한 SURF를 이용한 얼굴 인식 방법은 PCA를 이용한 방법보다 연산 시간이 더 요구되었지만, 인식률은 보다 더 높았다. 이러한 실험 결과를 통해, 특징점 추출 알고리즘도 얼굴 인식에 적용할 수 있음을 확인할 수 있었다.

• Bulletin of the Korean Chemical Society
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• 제27권10호
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• pp.1604-1608
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• 2006

A simple and efficient cloud point extraction-spectrofluorimetric method for the determination of thiamine in human urine is proposed. The procedure is based on the oxidation of thiamine with ferricyanide to form thiochrome, its extraction to Triton X-114 micelles and spectrofluorimetric determination. The variables affecting oxidation of thiamine, extraction and phase separation were studied and optimized. Under the experimental conditions used, the calibration graphs were linear over the range 2.5-1000 ng $mL^{-1}$. The limit of detection was 0.78 ng $mL^{-1}$ of thiamine and the relative standard deviation for 5 replicate determinations of thiamine at 400 ng $mL^{-1}$ concentration level was 2.42%. Average recoveries between 93-107% were obtained for spiked samples. The proposed method was applied to the determination of thiamine in human urine.

• Bulletin of the Korean Chemical Society
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• 제27권11호
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• pp.1780-1784
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• 2006

Cloud point extraction was used to extract mefenamic acid (MF) from human urine, and spectrofluorimetry and spectrophotometry were used to analyze extracted MF. The variables affecting extraction and phase separation, i.e. HCl and Triton X-114 concentration, temperature and time of equilibration, were optimized. Under the experimental conditions used the limit of detection for extraction of 25 mL of sample was 0.006 and 0.045 mg $L^{-1}$, with relative standard deviations of 2.52 and 1.45% (n = 5) for spectrofluorimetric or spectrophotometric methods, respectively. Good recoveries in the range of 95-107% were obtained for spiked samples. The proposed methods were applied to the determination of MF in human urine.

• Bulletin of the Korean Chemical Society
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• 제32권8호
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• pp.2637-2642
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• 2011

A new ultrasonic-assisted micellar extraction and cloud-point pre-concentration method was developed for the determination of major saikosaponins, namely saikosaponins -A, -C and -D, in Radix Bupleuri by high performance liquid chromatography with evaporative light scattering detection (HPLC-ELSD). The non-ionic surfactant Genapol X-080 (oligoethylene glycol monoalkyl ether) was chosen as the extraction additive and parameters affecting the extraction efficiency were optimized. The highest yield was obtained with 10% (w/v) Genapol X-080, a liquid/solid ratio of 200:1 (mL/g) and ultrasonic-assisted extraction for 40 min. In addition, the optimum cloud-point pre-concentration was reached with 10% sodium sulfate and equilibration at $60^{\circ}C$ for 30 min. Separation was achieved on an Ascentis Express C18 column (100 ${\times}$ 4.6 mm i.d., 2.7 ${\mu}M$) using a binary mobile phase composed of 0.1% acetic acid and acetonitrile. Saikosaponins were detected by ELSD, which was operated at a $50^{\circ}C$ drift tube temperature and 3.0 bar nebulizer gas ($N_2$) pressure. The water-based solvent modified with Genapol X-080 showed better extraction efficiency compared to that of the conventional solvent methanol. Recovery of saikosaponins ranged from 93.1 to 101.9%. An environmentally-friendly extraction method was successfully applied to extract and enrich major saikosaponins in Radix Bupleuri.