• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2733-2737
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• 2014

Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.267-274
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• 2009

Recently, UAVs (Unmanned Aerial Vehicles) are expected much as the Unmanned Systems for various missions. These missions are often based on the Vision System. Especially, missions such as surveillance and pursuit have a process which is carried on through the transmitted vision data from the UAV. In case of small UAVs, monocular vision is often used to consider weights and expenses. Research of missions performance using the monocular vision is continued but, actually, ground and target model have difference in distance from the UAV. So, 3D distance measurement is still incorrect. In this study, Mean-Shift Algorithm, Optical Flow and Subspace Method are posed to estimate the relative depth. Mean-Shift Algorithm is used for target tracking and determining Region of Interest (ROI). Optical Flow includes image motion information using pixel intensity. After that, Subspace Method computes the translation and rotation of image and estimates the relative depth. Finally, we present the results of this study using images obtained from the UAV experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.421-427
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• 2011

The importance of the real-time object recognition and tracking field has been growing steadily due to rapid advancement in the computer vision applications industry. As is well known, the mean-shift algorithm is widely used in robust real-time object tracking systems. Since the mentioned algorithm is easy to implement and efficient in object tracking computation, many say it is suitable to be applied to real-time object tracking systems. However, one of the major drawbacks of this algorithm is that it always converges to a local mode, failing to perform well in a cluttered environment. In this paper, an Optical Flow-based algorithm which fits for real-time recognition of multiple moving objects is proposed. Also in the tests, the newly proposed method contributed to raising the similarity of multiple moving objects, the similarity was as high as 0.96, up 13.4% over that of the mean-shift algorithm. Meanwhile, the level of pixel errors from using the new method keenly decreased by more than 50% over that from applying the mean-shift algorithm. If the data processing speed in the video surveillance systems can be reduced further, owing to improved algorithms for faster moving object recognition and tracking functions, we will be able to expect much more efficient intelligent systems in this industrial arena.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1933-1934
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• 2006

이 논문은 비강체 객체에 대한 실시간 추적시 다른 객체에 의한 간섭의 영향을 줄이는 방법을 제시한다. 제시한 방법에서 객체 추적에 대한 알고리즘은 현재 프레임에서 확률적으로 목표의 위치를 찾는 Mean shift 방법에 기초를 두고 있다. 기존의 방법에서는 mean shift 의 파라미터로서 색분포만 사용한다. 하나의 파라미터에만 의존하므로 같은 색분포를 갖는 다른 객체가 추적 영역 내에 들어오게 되면 새로운 객체를 기존 객체로 인식하게 되는 문제가 발생한다. 여기서 우리는 강인한 객체추적을 하기 위해 다른 하나의 파라미터로서 거리정보를 이용을 제안한다. 거리정보에 최적화된 흐름 추정(optical flow estimation)방법을 확장 도입한 강인한 에러 기준(robust error norm) 방법을 사용하여 기존의 객체에게 더 많은 가중치를 주는 방식으로 mean shift 추적 방법을 기초로 하여 강력하게 추적하는 방법을 제안한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.729-732
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• 2014

본 논문에서는 실시간 영상에서 움직임 검출 및 추적에 관련한 기본 기술들을 나열하고 구현하여 구현 가능성 및 성능에 대하여 검증을 진행하였다. 움직임 검출에는 배경 차영상 기법에 의한 움직임 및 변화 영역 검출 방법과 움직임 히스토리에 의한 움직임 검출법, 광류에 의한 움직임 검출법이 있으며 이를 구현하여 검증하였다. 또한 움직임 추적의 경우에는 추적하려는 물체의 히스토그램의 역투영을 이용하면서 물체의 중심점을 추적하는 MeanShift와 물체의 중심, 크기, 방향을 함께 추적하는 CamShift가 있고 Kalman 필터에 의한 움직임 추적을 구현하여 검증하였다. 구현된 방법을 통하여 보안용의 영상감시 장비의 추적 시스템 및 GPS 좌표를 기반으로하여 비행체를 추적하면서 통신링크를 유지하는 추적안테나 시스템에 적용하므로서 제어의 정확도를 높일 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.206-208
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• 2000

본 논문은 칼라 정보와 움직임 정보를 이용한 객체 분할 기법의 설계에 대하여 소개한다. 객체 분할 알고리즘은 L*u*v 공간의 칼라 특성과 움직임 특성을 결합하여 설계하였다. 즉 공간 분할은 mean shift 칼라 클러스터링 알고리즘(color clustering algorithm)을 사용하여 중심 칼라 영역에 따라 동일한 칼라 지역으로 통합한다. 시간 분할은 움직임 검출을 위하여 affine six parameter 움직임 모델과 optical flow equation를 이용하여 움직임이 발생한 부분을 검출한다. 다음에 공간 분할과 시간 분할에 따라 결과를 통합하고 MAD(mean absolute difference)를 사용하여 객체를 추출하는 알고리즘을 설계하였다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.4
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• pp.270-274
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• 2015

We suggest that HSV Color Space may be used to detect a vehicle detecting system at nighttime. It is essential that a licence plate should be extracted when a vehicle is under surveillance. To do so, a licence plate may be enlarged to certain size after the aimed vehicle is taken picture from a distance by using Pan-Tilt-Zoom Camera. Either Mean-Shift or Optical Flow Algorithm is generally used for the purpose of a vehicle detection and trace, even though those algorithms have tendency to have difficulty in detection and trace a vehicle at night. By utilizing the fact that a headlight or taillight of a vehicle stands out when an input image is converted in to HSV Color Space, we are able to achieve improvement on those algorithms for the vehicle detection and trace. In this paper, we have shown that at night, the suggested method is efficient enough to detect a vehicle 93.9% from the front and 97.7% from the back.

• Journal of the Optical Society of Korea
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• v.19 no.6
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• pp.705-710
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• 2015

The fabrication process of thin boron-doped nanocrystalline diamond (B-NCD) microelectrodes on fused silica single mode optical fiber cladding has been investigated. The B-NCD films were deposited on the fibers using Microwave Plasma Assisted Chemical Vapor Deposition (MW PA CVD) at glass substrate temperature of 475 ℃. We have obtained homogenous, continuous and polycrystalline surface morphology with high sp³ content in B-NCD films and mean grain size in the range of 100-250 nm. The films deposited on the glass reference samples exhibit high refractive index (n=2.05 at λ=550 nm) and low extinction coefficient. Furthermore, cyclic voltammograms (CV) were recorded to determine the electrochemical window and reaction reversibility at the B-NCD fiber-based electrode. CV measurements in aqueous media consisting of 5 mM K₃[Fe(CN)₆] in 0.5 M Na₂SO₄ demonstrated a width of the electrochemical window up to 1.03 V and relatively fast kinetics expressed by a redox peak splitting below 500 mV. Moreover, thanks to high-n B-NCD overlay, the coated fibers can be also used for enhancing the sensitivity of long-period gratings (LPGs) induced in the fiber. The LPG is capable of measuring variations in refractive index of the surrounding liquid by tracing the shift in resonance appearing in the transmitted spectrum. Possible combined CV and LPG-based measurements are discussed in this work.