• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.5
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• pp.40-47
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• 2009

A motion adaptive video noise reduction scheme is proposed by cascading a temporal filter and a spatial filter. After a noise-robust motion detection is performed with a pre-spatial filter, the strength of the motion adaptive temporal filter is controlled by the amount of temporal movement. In order to fully utilize the temporal correlation of video signal, noisy input image is processed first by the temporal filter, therefore, image details of temporally stationary region are quite well preserved while undesired noises are suppressed. In contrast to the pre-spatial filter used for the robust motion detection, the cascaded post-spatial filter removes the remained noises by considering the strength of the temporal filter and the spatial self-similarity search results obtained from the pre-spatial filter.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.635-638
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• 1999

도로 위에 설치된 카메라에서 검지 영역의 데이터를 입력받아 통과 차량수, 도로 점유율, 차량속도, 차간 거리 등의 교통정보를 실시간으로 산출하는 기법은 지능형 교통정보 시스템(ITS)의 핵심 분야이다. 본 논문에서는 검지영역의 시공간 영상 분석에 의해 다양한 기상 조건과 그림자 등의 환경의 변화에 민감하지 않은 교통정보 산출기법을 제안한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.77-81
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• 1996

In order to conform to the needs of effective program production in multimedia era, we are studying Desk Top Program Production system. With the DTPP, users can easily produce multimedia program including video, sound, and ancillary data, and freely handle video images synthesizing video components retrieved from video database. This paper describes the new program production system, DTPP and its key technologies such as cooperative program production via multimedia network, indexing and utilization of attribute information of images, and image segmentation and spatio-temporal editing.

• Journal of Broadcast Engineering
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• v.15 no.4
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• pp.474-486
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• 2010

In this paper, we propose a new method for detection moving object contour using spatial and temporal edge. In general, contour pixels of the moving object are likely present around pixels with high gradient value along the time axis and the spatial axis. Therefore, we can detect the contour of the moving objects by finding pixels which have high gradient value in the time axis and spatial axis. In this paper, we introduce a new computation method, termed as temporal edge, to compute an gradient value along the time axis for any pixel on an image. The temporal edge can be computed using two input gray images at time t and t-2 using the Sobel operator. Temporal edge is utilized to detect a candidate region of the moving object contour and then the detected candidate region is used to extract spatial edge information. The final contour of the moving object is detected using the combination of these two edge information, which are temporal edge and spatial edge, and then the post processing such as a morphological operation and a background edge removing procedure are applied to remove noise regions. The complexity of the proposed method is very low because it dose not use any background scene and high complex operation, therefore it can be applied to real-time applications. Experimental results show that the proposed method outperforms the conventional contour extraction methods in term of processing effort and a ghost effect which is occurred in the case of entropy method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1319-1324
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• 2002

In this paper, we present a new technique for extraction of moving objects in moving image sequence. The detection method of change regions is based on spatial gradient difference and temporal difference. Moving objects are extracted by motion information and prediction error of each region. In the simulation results, the proposed technique shows good performance.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1350-1352
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• 1996

The purpose of image sequence coding is to reduce the spatio-temporal redundancies. For the spatial redundancies, we can use the transform coding such as DCT. In this paper, the optical flow method is applied to solve the problem of temporal redundancies. There are several estimation methods like block matching method and pel-recursive method. Block matching method is easy for a hardware implementation because of the computational simplicity. So, it is now used as the estimation method in MPEG-l, MPEG-2, and H.261. We compared the merits and demerits of the optical flow method and the block matching method in this paper.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.19-28
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• 2019

Images captured by drone have the advantage of quickly constructing spatial information in small areas and are applied to fields that require quick decision making. If an image registration technique that can automatically register the drone image on the ortho-image with the ground coordinate system is applied, it can be used for various analyses. In this study, a methodology for geo-referencing of a single image and sequential images using drones was proposed even if they differ in spatio-temporal resolution using linear features and distinct points. Through the method using linear features, projective transformation parameters for the initial geo-referencing between images were determined, and then finally the geo-referencing of the image was performed through the template matching for distinct points that can be extracted from the images. Experimental results showed that the accuracy of the geo-referencing was high in an area where relief displacement of the terrain was not large. On the other hand, there were some errors in the quantitative aspect of the area where the change of the terrain was large. However, it was considered that the results of geo-referencing of the sequential images could be fully utilized for the qualitative analysis.

• Journal of radiological science and technology
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• v.42 no.2
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• pp.119-130
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• 2019

Positron emission tomography (PET) is widely used imaging modality for effective and accurate functional testing and medical diagnosis using radioactive isotopes. However, PET has difficulties in acquiring images with high image quality due to constraints such as the amount of radioactive isotopes injected into the patient, the detection time, the characteristics of the detector, and the patient's motion. In order to overcome this problem, we have succeeded to improve the image quality by using the dynamic image reconstruction method based on singular value decomposition. However, there is still some question about the characteristics of the proposed technique. In this study, the characteristics of reconstruction method based on singular value decomposition was estimated over computational simulation. As a result, we confirmed that the singular value decomposition based reconstruction technique distinguishes the images well when the signal - to - noise ratio of the input image is more than 20 decibels and the feature vector angle is more than 60 degrees. In addition, the proposed methode to estimate the characteristics of reconstruction technique can be applied to other spatio-temporal feature based dynamic image reconstruction techniques. The deduced conclusion of this study can be useful guideline to apply medical image into SVD based dynamic image reconstruction technique to improve the accuracy of medical diagnosis.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.120-126
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• 2005

This paper presents the 3D wavelet based video compression system using quad-tree algorithm. The 3D wavelet based video compression system removes the temporal correlation of the input sequences using the motion compensation filter and decomposes the spatio-temporal subband using the spatial wavelet transform. The proposed system allocates the higher bit rate to the low frequency image of the 3D wavelet sequences and improves the 0.64dB PSNR performance of the reconstructed image in comparison with that of H.263. In addition to the limitation on the propagation of the motion compensation error by the 3D wavelet transform, the proposed system progressively transmits the input sequence according to the resolution and rate scalability.