• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.812-820
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• 2012

In this paper, multiple pedestrians tracking system using Histogram of Oriented Gradient and occlusion detection is proposed. The proposed system is applicable to Intelligent Surveillance System. First, we detect pedestrian in a image sequence using pedestrian's feature. To get pedestrian's feature, we make block-histogram using gradient's direction histogram based on HOG(Histogram of Oriented Gradient), after that a pedestrian region is classified by using Linear-SVM(Support Vector Machine) training. Next, moving objects are tracked by using position information of the classified pedestrians. And we create motion trajectory descriptor which is used for content based event retrieval. The experimental results show that the proposed method is more fast, accurate and effective than conventional methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.137-145
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• 2014

This paper suggests an LDA-based long distance face recognition algorithm for intelligent surveillance system. The existing face recognition algorithm using single distance face image as training images caused a problem that face recognition rate is decreased with increasing distance. The face recognition algorithm using face images by actual distance as training images showed good performance. However, this also causes user inconvenience as it requires the user to move one to five meters in person to acquire face images for initial user registration. In this paper, proposed method is used for training images by using single distance face image to automatically create face images by various distances. The test result showed that the proposed face recognition technique generated better performance by average 16.3% in short distance and 18.0% in long distance than the technique using the existing single distance face image as training. When it was compared with the technique that used face images by distance as training, the performance fell 4.3% on average at a close distance and remained the same at a long distance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2267-2273
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• 2009

In this paper, in order to monitor and manage an electrical risk factor like as leakage current, load current, and arc-fault, a real time monitoring and management system being operated in the ubiquitous environment was developed, and a plan of construction of an electrical safety grid using the system was proposed. For confirmation of usefulness and reliability of the proposed safety system and grid, the developed intelligent panels were applied to 28 Korean traditional houses in Jeonjoo city, and the grid including the panels was operated. If the proposed National Electrical Safety Grid is completely constructed in the houses of general electrical users, the Grid will have an effect on that a main manager on electrical safety transfers from management system by general people to real-time management system by expert. As a result, the electrical fires caused by an over-load, an arc-fault, and an earth-fault will be prevented.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.149-162
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• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.50-50
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• 2022

한국농어촌공사 산하의 농업용저수지 중 3786개소에 대한 수질조사를 '19년도에 실시한 결과, TOC 기준 4등급 초과 저수지 비율은 약 20%로써, 도심 근교 저수지에서 녹조현상 빈발로 인해 수질, 악취, 미관 등의 환경문제 개선 민원이 다수 발생하고 있다. 현재 녹조 발생 사후관리를 위해 주로 사용되고 있는 대형 조류제거선은 저수심 수변부에서의 적용성에 한계가 있고, Al 기반의 응집제를 사용하여 조류를 수거해서 폐기하고 있는 실정이다. (주)이엔이티는 농어촌연구원, (주)코레드, (주)삼호인넷과 함께 호소나 정체하천의 수변지역에 적용될 수 있는 저에너지형 유해조류 포집시스템 개발과, 수거된 조류부산물을 무독화하여 농업재료로 재활용하는 방안을 연구하고 있다. 저수지나 정체수역의 녹조는 바람, 수면유동 등에 의해 수변에 집적되는 특성이 있어, 인공지능 기술로 녹조현상을 감시하여 조류 밀집구간에 접근할 수 있는 자율이동식 수상이동장치를 개발 중이다. 수상이동장치는 조류포집장치를 탑재하기 위한 부력체, 원격 운전이 가능한 무인항법장치, 수변식생대 및 저수심지역 이동을 고려한 수차방식 추진체, 전체 장치의 전원 공급을 위한 고성능 배터리 등으로 구성하여 상세 도면 설계를 진행하고 있다. 조류포집장치에는 표층에 주로 분포하는 남조류를 선택 흡입하는 포집 부표를 적용하였고, Al계 응집제 사용을 배제한 분리막 실험을 통해 침지형 막분리조 및 가압형 농축조를 설계하였다. 유해조류 포집 및 농축은 수상에서 이동체에 탑재하여 이뤄지고, 육상에서는 자원 회수가 가능하도록 회분식 응집공정으로 구분하였다. 조류 밀집지역에서 수거된 조류의 무독화 및 농업재료 자원화 타당성 평가를 위해 특용 버섯균주를 활용한 시료별 분석항목을 선정하고 실험 매트릭스에 따라 실증실험을 수행하였다. 수거조류를 전처리하여 성분 및 발열량을 분석하고 버섯재배 전후의 마이크로시스틴 독소(LR, RR, LR)를 포함한 성분 분석을 수행하여, 고체연료, 비료 및 사료로 활용방안을 검토하였다. 무인자율이동 조류포집장치는 실증화 규모로 제작하여 기선정된 테스트베드에서 현장적용성 평가를 수행할 예정이다. 본 연구를 통해 개발된 유해조류 포집 시스템은 기존의 녹조제거 방안을 보완하여 정체수역의 생태계 복원 및 친수공간의 환경개선 등에 적용되며, 무독화가 입증된 유해조류의 농업재료 자원화 기술은 고부가 상품 개발 및 환경폐기물 감축에 활용될 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2480-2487
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• 2011

As sensor technology grows up in fields such as environmental hazards detecting system, ubiquitous sensor network, intelligent robot, the sensing and detecting system for sensor is increasing. The sensor data is measured by change of chemical and physical status. Because of decrepit sensor or various sensing environment, it is problem that sensor data is inaccurate result. So the reliability of sensor data is essential. In this paper, we proposes a reliable sensor signal processing platform for various sensor. To improve reliability, we use same sensors in multiple array structure. As sensor data is corrected by spatial and temporal relation signal processing algorithm for measured sensor data, reliability of sensor data can be improved. The exclusive protocol between platform components is designed in order to verify sensor data and sensor state in various environment.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.57-67
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• 2010

Smart grid technology can expand energy efficiency into the home by monitoring consumer energy usage in real time and communicating with household devices that respond to demands to shut off during periods of non-use, allowing individual consumers to control their electricity usage more effectively. But, the information collected on a smart grid will form a library of personal information, the mishandling of which could be highly invasive of consumer privacy. There will be major concerns if consumer-focused principles of transparency and control are not treated as essential design principles from beginning to end. In this paper, using. All-Or-Nothing Transform encryption mode for providing smart grid security, we propose efficient distributed data Management based on XOR operation. The contribution of this paper is to provide a secure algorithm that manages efficiently distributed data in the field of private data in smart grid environment.