• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1911-1915
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• 2010

영상수위계는 카메라에 의해서 수위표를 촬영하여 촬영된 영상을 처리하여 수위값으로 변환하여 자동적으로 수위를 측정하는 장비이다. 이 수위계는 기존 수위측정 장비인 부자식, 압력식, 기포식, 초음파식, 레이다식과는 달리 수위표를 촬영한 영상으로부터 수위를 직접 눈으로 확인할 수 있는 장점이 있다. 이로 인해 영상자료로부터 측정된 수위를 검증할 수 있어 수위측정의 정확도를 향상시킬 수 있다. 그리고 수위표 영상과 더불어 관측지점 주변의 전체 영상을 동시에 촬영하여 실시간으로 전송하기 때문에 홍수시 하천 상황에 대한 모니터링 목적으로 사용될 수 있다. 수위관측용으로 운영 중인 영상수위계의 수위측정자료를 분석한 결과, 안개가 짙게 낀 경우, 목자판이 오염된 경우, 목자판 내에 그림자가 진 경우 등에서 수면을 인식하지 못하거나 오인식이 발생하였다. 이와 같이 수위 오 결측이 발생하는 경우에 수면을 정확하게 인식할 수 있도록 수위 측정방법을 개선하였다. 영상의 분할 이진화 처리기법, 노이즈 제거 기법, 목자판 영역내의 영상농도에 대한 히스토그램을 통해서 목자판과 수면을 구분하는 기법을 영상처리방법으로 새롭게 적용하였다. 수위 오 결측이 발생하는 영상자료를 이용하여 개선된 영상처리방법의 성능을 검증한 결과, 기존 방법으로는 수면을 전혀 인식하지 못하였던 영상이 개선된 방법을 적용하면 안개가 낀 경우에 약 97%까지, 목자판이 오염된 경우에 약 89%까지, 목자판 내에 그림자가 진 경우에 약 92%까지 수면을 인식하였다. 따라서 이와 같이 개선된 방법을 적용하게 되면 영상수위계의 정확도를 향상시킬 수 있을 것으로 기대된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.133-140
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• 2017

In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.6
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• pp.819-826
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• 2002

Cellular neural networks(CNN) are neural networks that have locally connected characteristics and real-time image processing. Locally connected characteristics are suitable for VLSI implementation. It also has applications in such areas as image processing and pattern recognition. In this thesis cellular neural networks are used for feature detection in number recognition at the stage of re-processing. The four or six directional shadow detectors are used in numbers recognition. At the stage of classification, this result of feature detection was simulated by using a multi-layer back Propagation neural network. The experiments indicate that the CNN feature detectors capture good features for number recognition tasks.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.4
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• pp.237-241
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• 2011

Stable operation of an industry crane becomes more important as current industry facilities become larger and operate at higher speeds. This paper proposes implementing a system for monitoring moving objects within safety lines of an industry crane by camera. The cost of implementing such a system is low, since it requires only a webcam and notebook computer. The detection algorithm of moving objects uses the feature extraction method by image differential histograms. The proposed system is robust to variations in the weather and environment. The area of the inside safety lines is considered and shadow removal algorithm is used for good performance of the system. The system is valuable for practical applications in the industry.

• The Journal of Korean Orthopaedic Ultrasound Society
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• v.3 no.2
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• pp.91-96
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• 2010

The artifacts in sonography is not always harmful. Sometimes it is beneficial for the evaluation of the water contents of the soft tissue and estimating the degree of inflammation and character of the regenerated tissue indirectly using artifacts such as acoustic shadowing and the enhanced transmission. It can also be useful to evaluate the possibility of aspiration of the calcifies masses by knowing of the contents of the water among them. Unlike the MRI it is useful to get real time informations with low cost in diagnosis and treatment of the soft tissue disease usinf artifacts in sonography.

• Archives of design research
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• v.19 no.4 s.66
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• pp.71-80
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• 2006

Collaboration has become essential in the product design process due to internationalized and specialized business environments. This study presents a real-time collaborative 3D design workspace for distributed designers, focusing on the development and the evaluation of new interaction techniques supporting nonverbal communication such as awareness of participants, shared manipulation and tele-presence. Requirements were identified in terms of shared objects, shared workspaces and awareness through literature reviews and an observational study. An Augmented Reality based collaborative design workspace was developed, in which two main interaction techniques, Turn-table and Virtual Shadow, were incorporated to support shared manipulation and tele-presence. Turn-table provides intuitive shared manipulation of 3D models and physical cues for awareness of remote participants. Virtual shadow supports natural and continuous awareness of location, gestures and pointing of partners. A lab-based evaluation was conducted and the results showed that interaction techniques effectively supported awareness of general pointing and facilitated discussion in 3D model reviews. The workspace and the interaction techniques can facilitate more natural communication and increase the efficiency of collaboration on virtual 3D models between distributed participants (designer-designer, engineer, or modeler) in collaborative design environments.

• The Journal of Bigdata
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• v.8 no.2
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• pp.73-82
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• 2023

With 78% of current fisheries workers being elderly, there's a pressing need to address labor shortages. Consequently, active research on smart aquaculture technologies, centered on object detection and tracking algorithms, is underway. These technologies allow for fish size analysis and behavior pattern forecasting, facilitating the development of real-time monitoring and automated systems. Our study utilized video data from cameras outside aquaculture facilities and implemented fish detection and tracking algorithms. We aimed to tackle high maintenance costs due to underwater conditions and camera corrosion from ammonia and pH levels. We evaluated the performance of a real-time system using YOLOv7 for fish detection and the SORT algorithm for movement tracking. YOLOv7 results demonstrated a trade-off between Recall and Precision, minimizing false detections from lighting, water currents, and shadows. Effective tracking was ascertained through re-identification. This research holds promise for enhancing smart aquaculture's operational efficiency and improving fishery facility management.

• Journal of the Korea Convergence Society
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• v.8 no.7
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• pp.7-13
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• 2017

Robot performances in public places are conducted for the purpose of promoting robot technology and inducing interest in events, exhibitions, and streets instead of dedicated stages. This paper extracts robot images in real time from a robot operation in front of a green chroma key cloth, and synthesizes them on various stage images. A simple and robust method for extracting a foreground robot from a chroma key background without a user's preset is proposed. After increasing the color difference between the background and the foreground, this method automatically removes the background based on the histogram of the difference information, thereby eliminating the need for a user's preset. The simulation shows 98.8% of foreground extraction rate and experimental results demonstrate that the robots can effectively be extracted from the background.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.293-297
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• 2007

This thesis suggests a new algorithm to detects multiple moving objects using a CMODE(Correct Multiple Object DEtection) method in the color images acquired in real-time and to track the interested pedestrian using motion and hue information. The multiple objects are detected, and then shaking trees or moving cars are removed using structural characteristics and shape information of the man , the interested pedestrian can be detected, The first similarity judgment for tracking an interested pedestrian is to use the distance between the previous interested pedestrian's centroid and the present pedestrian's centroid. For the area where the first similarity is detected, three feature points are calculated using k-mean algorithm, and the second similarity is judged and tracked using the average hue value for the $3{\times}3$ area of each feature point. The zooming of camera is adjusted to track an interested pedestrian at a long distance easily and the FOV(Field of View) of camera is adjusted in case the pedestrian is not situated in the fixed range of the screen. As a experiment results, comparing the suggested CMODE method with the labeling method, an average approach rate is one fourth of labeling method, and an average detecting time is faster three times than labeling method. Even in a complex background, such as the areas where trees are shaking or cars are moving, or the area of shadows, interested pedestrian detection is showed a high detection rate of average 96.5%. The tracking of an interested pedestrian is showed high tracking rate of average 95% using the information of situation and hue, and interested pedestrian can be tracked successively through a camera FOV and zooming adjustment.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.545-552
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• 2012

In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.