• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.191-194
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• 2009

본 논문에서는 효율적인 다시점 비디오 부호화를 위해 히스토그램(histogram)을 이용한 다시점 비디오의 휘도(luminance)와 색차(chrominance)성분 보상 기법을 제안한다. 다시점 비디오는 카메라의 기하학적인 위치 차이와 여러 대의 카메라가 동일한 특성을 가지도록 완벽히 조정되지 못함으로 인해 동일한 시간대에 촬영된 인접한 시점 영상 간에 휘도와 색상의 차이가 발생할 수 있다. 이러한 특성은 인접한 카메라로부터 획득된 영상을 참조하여 시점간 움직임 예측 시에 오정합의 원인이 되어 부호화 효율을 떨어뜨리게 된다. 본 논문에서는 효율적인 다시점 비디오 부호화를 위해 시점간의 히스토그램을 비교하여 정합하는 휘도 및 색차 보상 기법을 수행한다. 일정한 시간 대역(time interval)에서 다시점 비디오의 평균 누적 히스토그램을 이용하여 참조 영상을 생성하고 각 시점별로 정합 함수를 통해 다시점 영상 간의 휘도와 색상의 불일치성을 보상한다. 제안하는 조명 보상 기법을 통하여 다시점 비디오 부호화 효율을 높일 수 있었다.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.764-781
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• 2013

In this paper, we propose a highly precise vehicle detection method with low false alarm using billboard sweep stereo matching and multi-stage hypothesis generation. First, we capture stereo images from cameras established in front of the vehicle and obtain the disparity map in which the regions of ground plane or background are removed using billboard sweep stereo matching algorithm. And then, we perform the vehicle detection and tracking on the labeled disparity map. The vehicle detection and tracking consists of three steps. In the learning step, the SVM(support vector machine) classifier is obtained using the features extracted from the gabor filter. The second step is the vehicle detection which performs the sobel edge detection in the image of the left camera and extracts candidates of the vehicle using edge image and billboard sweep stereo disparity map. The final step is the vehicle tracking using template matching in the next frame. Removal process of the tracking regions improves the system performance in the candidate region of the vehicle on the succeeding frames.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.263-270
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• 2024

As unmanned aerial vehicles(UAVs) and sensors have been developed in a variety of ways, it has become possible to update information on the ground faster than existing aerial photography or remote sensing. However, acquisition and input of ground control points(GCPs) UAV photogrammetry takes a lot of time, and geometric distortion occurs if measurement and input of GCPs are incorrect. In this study, RGB-based orthophotos were generated to reduce GCPs measurment and input time, and comparison and evaluation were performed by applying feature point algorithms to target orthophotos from various sensors. Four feature point extraction algorithms were applied to the two study sites, and as a result, speeded up robust features(SURF) was the best in terms of the ratio of matching pairs to feature points. When compared overall, the accelerated-KAZE(AKAZE) method extracted the most feature points and matching pairs, and the binary robust invariant scalable keypoints(BRISK) method extracted the fewest feature points and matching pairs. Through these results, it was confirmed that the AKAZE method is superior when performing geometric correction of the objective orthophoto for each sensor.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.127-129
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• 2005

본 연구에서는 백라이트 유닛의 검사를 위한 머신비전 시스템을 구축한다. 시스템은 크게 하드웨어와 소프트웨어로 나눌 수 있고 하드웨어는 조명부, 영상획득부, 로봇 암 제어부로 분류된다. 조명부는 36W FPL램프로 구성되었고 조명부의 상판에 아크릴판을 거치대로 이용하여 백라이트 유닛을 거치한다. 로봇 암 제어부는 2축 로봇 암을 제어하여 로봇 암의 센서부착 지지대에 부착된 CCD 센서를 이동시킨다. 이와 동시에 영상획득부에서는 이미지를 획득하여 PC로 전송한다. 소프트웨어의 화상처리 검사 알고리즘은 일정 패턴이 있는 도광판에 대한 검사 알고리즘과 일정패턴이 없근 백라이트 유닛에 대한 검사 알고리즘으로 분리된다. 일정 패턴이 인쇄되어 있는 패널에 대한 검사 알고리즘은 모폴로지 연산을 이용하는 템플릿 체크방법과 블록 매칭 방법이 사용되었고 일정패턴이 없는 유닛에 대한 검사는 개선된 Otsu 방법을 이용하여 얼룩이나 흐릿한 결함에 대한 결함을 검출하였다. 실험결과 불균일한 결함과 밝기가 일정하지 않은 결함일지라고 90% 이상의 검출율로 뛰어난 성능을 입증하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.17 no.2
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• pp.97-104
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• 1999

Digital elevation models(DEMs) represent an important data base for orthophoto generation The quality of a DEM depends on the geometrical accuracy of the original point or line data. This study analyzes the effects of grid space and scanning resolution in DEM creation with image matching method. The less standard deviation of DEM error was introduced when we adopted small grid space, but no effects in scanning resolution. Based on the bias error analysis of the DEM, we found that the error of a large scale of aerial photograph was bigger than that of a small scale case, and that such error mainly came from the closed area in large scale photographs. In order to reduce the closed area, the experiment has been conducted using multi scale and different overlap of aerial photo images. The result shows that the size of closed area and the shaded area has been dramatically decreased due to the adoption of multi scale aerial images instead of a couple of stereo images.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.143-149
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• 2018

Recently, due to the large-scale damage of natural disasters caused by global climate change, a monitoring system applying remote sensing technology is being constructed in disaster areas. Among remote sensing platforms, the drone has been actively used in the private sector due to recent technological developments, and has been applied in the disaster areas owing to advantages such as timeliness and economical efficiency. This paper deals with the development of a preprocessing system that can map the drone image data in a near-real time manner as a basis for constructing the disaster monitoring system using the drones. For the research purpose, our system is based on the SURF algorithm which is one of the computer vision technologies. This system aims to performs the desired correction through the feature point matching technique between reference images and shot images. The study area is selected as the lower part of the Gahwa River and the Daecheong dam basin. The former area has many characteristic points for matching whereas the latter area has a relatively low number of difference, so it is possible to effectively test whether the system can be applied in various environments. The results show that the accuracy of the geometric correction is 0.6m and 1.7m respectively, in both areas, and the processing time is about 30 seconds per 1 scene. This indicates that the applicability of this study may be high in disaster areas requiring timeliness. However, in case of no reference image or low-level accuracy, the results entail the limit of the decreased calibration.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.102-113
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• 2014

This paper suggests a novel hardware architecture of a real-time rectification which is to remove vertical parallax of an image occurred in the pre-processing stage of stereo matching. As an off-line step, Matlab Toolbox which was designed by J.Y Bouguet, was used to calculate calibration parameter of the image. Then, based on the Heikkila and Silven's algorithm, rectification hardware was designed. At this point, to enhance the precision of the rectified image, floating-point unit was generated by using Xilinx Core Generator. And, we confirmed that proposed hardware design had higher precision compared to other designs while having the ability to do rectification in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1271-1280
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• 2012

In the recent parking assistant systems, finding out the distance to the object behind a car is often performed by the range sensors such as ultrasonic sensors, radars. However, the installation of additional sensors on the used vehicle could be difficult and require extra cost. On the other hand, the motion stereo technique that extracts distance information using only an image sensor was also proposed. However, In the stereo rectification step, the motion stereo requires good features and exacts matching result. In this paper, we propose a fast algorithm that extracts the accurate distance information for the parallel parking situation using the consecutive images that is acquired by a rear-view camera. The proposed algorithm uses the quadrangle transform of the image, the horizontal line integral projection, and the blocking-based correlation measurement. In the experiment with the magna parallel test sequence, the result shows that the line-accurate distance measurement with the image sequence from the rear-view camera is possible.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1931-1932
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• 2006

로봇이 어떤 물체를 인지하고 그 물체에 대해 어떤 작업을 하고자 할 때 특정 물체의 인식 문제, 3차원 정보를 획득하는 문제, 자세를 추정하는 문제 등 해결해야 될 문제들이 있다. 물체를 인식하는 과정에서는 주위 배경과 물체의 크기의 변화, 회전, 가려짐 등으로 인해 물체 인식을 어렵게 만드는 요소들이 있다. 2차원 이미지를 통해 3차원 정보를 추출하는 과정은 일반적으로 두 대의 카메라를 이용하여 스테레오 이미지를 통해 얻는다. 이 때 좌우 영상간의 매칭의 과정이 필요하다. 자세 추정의 문제는 카메라 좌표와 물체의 좌표간의 관계를 알아야 한다. Visual Servoing을 어렵게 만드는 많은 요인들이 있으며 본 논문에서는 물체의 크기, 회전, 이동에 불변인 디스크립터(descriptor)를 사용하는 SIFT(Scale Invariant Feature Transform)를 통해 3차원 물체의 인식과 자세를 추정하는 방법을 제시한다. 또한 자세 추정을 위해 2차원 Keypoint들의 매칭을 3차원 정보를 통해 검증하는 방법을 제시한다. (SIFT에 의해 추출된 point를 Keypoint라 명한다.)

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.217-222
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• 2017

Recent studies for working robot in dangerous places have been carried out on large unmanned ground vehicles or 4-legged robots with the advantage of long working time, but it is difficult to apply in practical dangerous fields which require the real-time system with high locomotion and capability of delicate working. This research shows the collaborated docking system of drone and ground vehicles which combines image processing algorithm and laser sensors for effective detection of docking markers, and is finally capable of moving a long distance and doing very delicate works. We proposed the docking system of drone and ground vehicles with sensor fusion which also suggests two template matching methods appropriate for this application. The system showed 95% docking success rate in 50 docking attempts.