• Journal of Periodontal and Implant Science
• /
• 제47권1호
• /
• pp.41-50
• /
• 2017

Purpose: The aims of the present study were to compare the image quality and visibility of tooth cracks between conventional methods and swept-source optical coherence tomography (SS-OCT) and to develop an automatic detection technique for tooth cracks by SS-OCT imaging. Methods: We evaluated SS-OCT with a near-infrared wavelength centered at 1,310 nm over a spectral bandwidth of 100 nm at a rate of 50 kHz as a new diagnostic tool for the detection of tooth cracks. The reliability of the SS-OCT images was verified by comparing the crack lines with those detected using conventional methods. After performing preprocessing of the obtained SS-OCT images to emphasize cracks, an algorithm was developed and verified to detect tooth cracks automatically. Results: The detection capability of SS-OCT was superior or comparable to that of trans-illumination, which did not discriminate among the cracks according to depth. Other conventional methods for the detection of tooth cracks did not sense initial cracks with a width of less than $100{\mu}m$. However, SS-OCT detected cracks of all sizes, ranging from craze lines to split teeth, and the crack lines were automatically detected in images using the Hough transform. Conclusions: We were able to distinguish structural cracks, craze lines, and split lines in tooth cracks using SS-OCT images, and to automatically detect the position of various cracks in the OCT images. Therefore, the detection capability of SS-OCT images provides a useful diagnostic tool for cracked tooth syndrome.

• 한국측량학회지
• /
• 제25권1호
• /
• pp.47-53
• /
• 2007

인공위성 영상을 이용하여 한반도 전역과 같이 넓은 지역에 대한 효율적인 영상 판독 및 분석 작업을 수행하기 위해서는 영상모자이크 작업이 필수적으로 요구된다. 본 논문은 영상모자이크 작업시 요구되는 접합선의 자동추출 기법과 이를 기반으로 한 자동 모자이크 영상제작 방법을 제시하였다. 인위적인 불연속을 최소화하는 접합선의 자동 추출기법으로는 검색영역에 대한 제약조건을 고려한 Minimum Absolute Gray Difference Sum 알고리즘과 Canny 에지검출 알고리즘을 함께 적용하였다. 또한 획득시기가 다른 인접영상간의 밝기 차이를 균일하게 유지시키기 위한 히스토그램 매칭 방법으로는 Match Cumulative Frequency 방법을 적용하였다. 본 연구의 결과 에지검출 기법을 통해 도로나 강 등과 같은 선형특성 지형 지물을 접합선으로 선정함으로서 인접영상간의 인위적인 불연속 형성을 최소화 할 수 있었다.

• 대한원격탐사학회지
• /
• 제35권6_2호
• /
• pp.1053-1065
• /
• 2019

신기후체제에 대응하여 정확한 탄소흡수 및 배출량을 산정하기 위해 토지이용 범주별 통계량 산출은 활동자료로서 매우 중요한 자료이다. 본 연구는 효과적인 토지이용 범주별 판독을 위하여 산림항공사진(이하 FAP)에 딥러닝모델을 적용하여 토지이용 범주별 자동화 판독 분류를 한 후 샘플링기법을 통해 국가단위 통계량을 산출하였다. 딥러닝모델에 적용한 데이터세트(이하, DS)는 국가산림자원조사 고정표본점 위치 기반 FAP의 이미지를 추출하여 훈련데이터세트(이하, 훈련DS)와 시험데이터세트(이하, 시험 DS)로 구분하였다. 훈련 DS는 토지이용 범주별 정의에 따라 이미지별 레이블을 부여하였으며, 딥러닝모델을 학습하고 검증하였다. 검증 시 모델의 학습정확도는 학습 횟수 1500회에서 정확도가 약 89%로 가장 높았다. 학습된 딥러닝모델을 시험DS에 적용한 결과, 이미지 레이블의 판독 분류정확도는 약 90%로 높았다. 샘플링기법을 통해 범주별 분류 결과에 대해 면적을 추정하여 국가통계와 비교한 결과 정합성 또한 높아 향후 LULUCF(Land Use, Land Use Change, Forestry)분야 국가 온실가스 인벤토리 보고서의 활동자료로 활용하기에 충분하다고 판단된다.

• 한국항행학회논문지
• /
• 제4권1호
• /
• pp.11-22
• /
• 2000

계기비행 시뮬레이터는 조종사들이 실제 비행 시 발생할 수 있는 여러 상황에 대비하여 각종 계기의 판독 및 조작 방법과 비행 절차 등을 숙달하기 위해 사용된다. 그러나 현재까지 개발된 시뮬레이터들은 실제 항공기와 동일한 환경의 구축에 주로 관심을 두었으나 비행에 필요한 다양한 기본적인 임무와 이착륙 절차 등에 관한 체계적 훈련과 훈련 결과에 대한 자동적인 평가 방안에 대해서는 연구가 미진한 실정이다. 따라서 본 논문에서는 계기비행 시뮬레이터에서 비행 중 임무, 이착륙 임무, 항로 비행과 같은 각종 비행 임무의 구현 및 평가 방법을 제시하도록 한다.

• 제어로봇시스템학회논문지
• /
• 제2권3호
• /
• pp.236-241
• /
• 1996

This paper presents a new eddy current testing system for inspecting tubes of steam generator in nuclear power plant. The proposed system adopted embedded expert system concept to automate tasks of the inspection such as inspection planning and flaw signal interpretation, and integrated all the tasks into a client/server type computing architecture using database management system. Therefore, human factor errors occurred during inspection could be minimized and the inspection data could be transferred in real-time. As a result, we can increase the level of inspection confidence and the productivity of a personal inspector. A prototype of the proposed system has been developed for 5 years and the test operation has been performed in domestic nuclear power plants.

• 한국기계가공학회지
• /
• 제3권3호
• /
• pp.24-31
• /
• 2004

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fine-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining, however, sensing and interpretation of signals ar more complex. In addition, the shafts of the mini-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm by LabVIEW was developed and the following results are obtained. It was possible to use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.493-493
• /
• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• 한국컴퓨터정보학회논문지
• /
• 제13권4호
• /
• pp.185-193
• /
• 2008

IT기반의 기상학과 기상 서비스의 급속한 발전에도 불구하고, 아직까지 사람들이 직접 기상 정보를 받아와 판단하는 전통적인 방식으로 기상 정보가 이용되고 있다. 특히 지능화된 기상 정보 처리가 유비쿼터스 컴퓨팅과 개개인의 생활에 매우 유용할 것으로 기대됨에도 불구하고, 기계 주도의 자동화된 기상정보 처리에 대한 연구는 오랫동안 주목을 받지 못했다. 본 논문에서는 지능형 기상 정보처리를 가능하게 하는 GRIB기반의 온톨로지의 설계에 대해서 논한다. GRIB은 세계적으로 널리 사용되는 범용 목적의 기상 데이터 포맷으로 세계 기상기구에 의해 승인된 형식이다. 설계된 온톨로지와 Jess 엔진으로 구성된 추론 시스템으로 지능형 기상 애플리케이션을 구현하고 실험하여, 기계 주도의 기상 정보 처리에 대한 효과를 검증하였다.

• Journal of Electrical Engineering and Technology
• /
• 제7권1호
• /
• pp.109-114
• /
• 2012

In this paper, we utilize training strategy of hidden Markov model (HMM) to use in versatile issues such as classification of time-series sequential data such as electric transient disturbance problem in power system. For this, an automatic means of optimizing HMMs would be highly desirable, but it raises important issues: model interpretation and complexity control. With this in mind, we explore the possibility of using genetic algorithm (GA) and harmony search (HS) algorithm for optimizing the HMM. GA is flexible to allow incorporating other methods, such as Baum-Welch, within their cycle. Furthermore, operators that alter the structure of HMMs can be designed to simple structures. HS algorithm with parameter-setting free technique is proper for optimizing the parameters of HMM. HS algorithm is flexible so as to allow the elimination of requiring tedious parameter assigning efforts. In this paper, a sequential data analysis simulation is illustrated, and the optimized-HMMs are evaluated. The optimized HMM was capable of classifying a sequential data set for testing compared with the normal HMM.

• 한국건설관리학회논문집
• /
• 제5권5호
• /
• pp.151-162
• /
• 2004

Current methods for construction site modeling employ large, expensive laser range scanners that produce dense range point clouds of a scene from different perspectives. Days of skilled interpretation and of automatic segmentation may be required to convert the clouds to a finished CAD model. The dynamic nature of the construction environment requires that a real-time local area modeling system be capable of handling a rapidly changing and uncertain work environment. However, in practice, large, simple, and reasonably accurate embodying volumes are adequate feedback to an operator who, for instance, is attempting to place materials in the midst of obstacles with an occluded view. For real-time obstacle avoidance and automated equipment control functions, such volumes also facilitate computational tractability. In this research, a human operator's ability to quickly evaluate and associate objects in a scene is exploited. The operator directs a laser range finder mounted on a pan and tilt unit to collect range points on objects throughout the workspace. These groups of points form sparse range point clouds. These sparse clouds are then used to create geometric primitives for visualization and modeling purposes. Experimental results indicate that these models can be created rapidly and with sufficient accuracy for automated obstacle avoidance and equipment control functions.