• 대한기계학회논문집A
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• 제21권10호
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• 한국정보통신학회논문지
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• 제15권7호
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• pp.1583-1590
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• 2011

기존 방사선 검색장치는 2차원 방사선 스캔 영상을 사용하기 때문에 정확성이 낮다는 것이 문제점으로 지적되어왔다. 본 연구에서는 컨테이터 X-선 검색 영상에 대한 스테레오 영상처리 기술의 적용 가능성을 분석하였다. 일반적 방사선 검색장치에 라인 센서 하나만을 추가하여 새롭게 고안한 스테레오 영상획득 장치로부터 검사 오브젝트의 좌우 시차 정보를 달리하는 두 장의 이차원 방사선 스캔영상을 획득하였다. 획득 영상에 대해서 매칭 알고리즘을 이용하여 3차원 오브젝트 복원하는 과정을 진행하였다. 오브젝트의 투과밀도 정보인 방사선 영상의 특성상 일반 스테레오 영상처리 알고리즘 적용은 한계가 발생하였다. 이를 극복하기 위해 먼저 이차원 영상의 에지정보에 기반한 3차원 영상복원을 시도하였다. 또한 새로운 볼륨복원 방식의 3차원 복원 알고리즘을 제안하였고, 실험을 통해 오브젝트 검색에서 개선된 형상복원 방법임을 확인하였다. 제안된 기술은 제한된 스캔환경에서 CT나 MRI 적용이 어려운 오브젝트에 대해 응용이 가능할 것이다.

• 디지털융복합연구
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• 제10권11호
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• pp.383-387
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• 2012

스캔된 인보이스에 특화된 서류 관리 자동화 시스템 구축에있어서 추출된 금전적 데이터의 정확도에대한 엄격한 요구는 인보이스 테이블을 위한 발생적 모델 설계에서 자체 인증 절차를 포함하는 것을 필요로 한다. 가격 = 단가 ${\times}$ 구매수량과 같은 내부적 관계식을 활용한 단순한 인증 절차를 사용하는 것이 전형적 방법론이다. 본 논문에서 는 영상내 테이블 헤더 부분의 탐색과 탐색된 헤더의 컬럼 구분자를 활용하는 개선된 자동 인증 절차를 갖춘 인보이스내 정보 추출 모델을 제안한다.

• Journal of Biosystems Engineering
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• 제40권2호
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• pp.153-158
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• 2015

Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.

• 대한산업공학회지
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• 제28권2호
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• pp.162-170
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• 2002

Detecting straight lines in an image is frequently required for various machine vision applications such as restoring CAD drawings from scanned images and object recognition. The standard Hough transform has been dominantly used to that purpose. However, massive storage requirement and low precision in estimating line parameters due to the quantization of parameter space are the major drawbacks of the Hough transform technique. In this paper, to overcome the drawbacks, an iterative algorithm based on a self-organizing map is presented. The self-organizing map can be adaptively learned such that image points are clustered by prominent lines. Through the procedure of the algorithm, a set of lines are sequentially detected one at a time. The algorithm can produce highly precised estimates of line parameters using very small amount of storage memory. Computational results for synthetically generated images are given. The promise of the algorithm is also demonstrated with its application to two natural images of inserts.

• Journal of information and communication convergence engineering
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• 제7권3호
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• pp.366-371
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• 2009

A realization for an accurate position detecting system of a moving target in two dimensional plane using dual line CCDs and photometric interpolation is presented. The system is realized that the infrared LEDs are utilized for lighting source, a target size is recognized by the scanned data from CCD owing to blocking the radiated light path by placing the target between CCD and lighting source, a coordinate on the plane is found by plane trigonometry formed by the moving target and two CCD sensors, and the former scan data is used for the coordinate iteratively and the photometric interpolation is applied to sub-pixel of scanned image. The experimental results show that the experiment results in a success rate about 3 different size targets, 3, 5 and 7mmm on the test plane $210{\times}373mm$. The moving target positioning detected success rate is 93% in 3mm target, 5mm is 95.3%, and 7mm is 95.8% respectively. The photometric interpolation is enhanced to 1.5% in comparison to be unused.

• Spatial Information Research
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• 제3권2호
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• pp.179-189
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• 1995

벡터링 도구를 이용하여 원판과 같은 양질의 도면이 없는 기존 지도를 수치화하기 위해서는 지도로부터 의미있는 벡터링 대상물(도로, 등고선, 해안선, filled-area, 문자, 기호 등)을 추출하는 방법이 필요하다. 본 논문에서는, 칼라지도로부터 추출해야 할 벡터링 대상물을 크게 곡선 미 직선, filled-area, 문자/기호로 분류하였으며, 대상물의 기하학적 특성과 칼라의 분포특성을 반영한 효율적인 벡터링 대상물 추출방법을 연구하였다. 곡선 및 직선 추출을 위해, 선의 연결성과 기하학적 특성을 반영한 방향성 마스크를 설계하고 이를 이용한 선추적 방법을 개발하였다. filled-area와 문자/기호의 경유에는 NxN 블럭간의 칼라분포 유사도 비교방법과 lical thresholding 방법을 각각 이용하여 벡터링 도구에서 수용할 수 있게 해줌으로써 소규모 지리정보 응용시스템을 보다 경제적으로 구축하는데 활용될 수 있을 것이다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(4)
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• pp.199-202
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• 2001

A current TV-OUT format is quite different from that of HDTY or PC monitor in encoding techniques. In other words, a conventional analog TV uses interlaced display while HDTV or PC monitor uses Non-interlaced / Progressive-scanned display. In order to encode image signals coming from devices that takes interlaced display format for progressive scanned display, a hardware logic in which scanning and interpolation algorithms are implemented is necessary. The ELA (Edge-Based Line Average) algorithm have been widely used because it provided good characteristics. In this study, the ADI(Adaptive De-interlacing Interpolation) algorithm using to improve the algorithm which shows low quality in vertical edge detections and low efficiency of horizontal edge lines. With the De-interlacing ASIC chip that converts the interlaced Digital YUV to De-interlaced Digital RGB is designed. The VHDL is used for chip design.

• 한국가시화정보학회:학술대회논문집
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• 한국가시화정보학회 2005년도 추계학술대회 논문집
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• pp.6-10
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• 2005

PIV(Particle image velocimetry) presents the flow velocity of whole flow fields in a fraction of a second. Conventional PIV method uses two optical axis configuration during the image grabbing process. That is, the illumination plane and the recording plane must be parallel. This configuration is very natural to grab the whole field without the image distortion. In the real problem, it is often to meet the situation which this configuration is hard to be fulfilled. In this study, we developed new PIV method which only uses single optical axis to grab the particle images. This new PIV method become possible by utilizing the scanning method similar to echo PIV technique. One particle image of scanning PIV consists of scanned several line images and by repeating this scanning process, two particle images were grabbed and processed to produce the velocity vectors.

• 대한기계학회논문집B
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• 제31권2호
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• pp.181-187
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• 2007

Conventional PIV method uses two optical axis configuration during the image grabbing process. That is, the illumination plane and the recording plane must be parallel. This configuration is very natural to grab the whole field without the image distortion. In the real problem, it is often to meet the situation when this configuration is hard to be fulfilled. In the present study, the new PIV method which uses only single optical axis to grab the particle images is developed. This new PIV method becomes possible by utilizing the scanning method similar to the echo PIV technique. One particle image of the scanning PIV consists of scanned several line images and by repeating this scanning process, two particle images were grabbed and processed to produce the velocity vectors. An optimization study was performed to find parameters which minimize the measurement errors. The effects of particle diameter, beam overlap ratio and particle number density were investigated.