• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.588-593
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• 2014

Recently, the smart devices has been possessed by a large majority of the adult, and offered various personalization services. This paper proposed the lightweight Intelligent Image Security System that notice the existence of any intruder in real time at the place of requiring the security by using smart device. The proposed image security system recognized whether or not intruder exists using the difference frame on the basis of Integral Image and the dynamic background updating algorithms. The intrusion notification is achieved by using the GCM push server that send massages in the application unit of user mobile device, and the SMTP mail server which is use of e-mail standard protocol. In case of the occurrence of intruder, GCM push server send an push-massage by the private mobile device, and SMTP mail server send the intruder's photograph and intrusion time. By the convergence of the various image processing algorithms and the performance of smart device, The proposed image security system can be applied to the various Intelligent Image Security field.

• Journal of Broadcast Engineering
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• v.27 no.6
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• pp.897-905
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• 2022

Research for video key frame detection has been actively conducted in the fields of computer vision. Recently with the advances on deep learning techniques, performance of key frame detection has been improved, but the various type of video content and complicated background are still a problem for efficient learning. In this paper, we propose a novel method for key frame detection, witch utilizes contrastive learning and memory bank module. The proposed method trains the feature extracting network based on the difference between neighboring frames and frames from separate videos. Founded on the contrastive learning, the method saves and updates key frames in the memory bank, witch efficiently reduce redundancy from the video. Experimental results on video dataset show the effectiveness of the proposed method for key frame detection.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.35-38
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• 2003

In this paper, I propose an automatic background extraction method and continuous background updating technique. Because there is a movement of a vehicle and a change of a background is feeble, the area moving through the time axis is looked for and a background and a vehicle image is divided. A way to give dynamically the threshold which divides the image frame into a vehicle image and the background in a space is enforced. Through the repetition of the above-mentioned process, the background pictorial image is gained. Using the karlman filter technique, the update is done so that a background image can obey a climate situation and an environmental change in day and night. A background image processed algorithm is better than the existent one. Through simulation, the feasibility of the algorithm has been verified.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2004.03a
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• pp.587-592
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• 2004

현재 원격탐사 자료는 각 분야 혹은 기관별로 개별적으로 자료 관리, 정보 생산이 이루어지고 있어 활용성이 저하되고 있으며 목적에 따라 활용하는 자료가 다양한 상황에서 활용분야별 특성을 고려한 기술 개발 및 기반구축의 필요성이 대두되고 있다. 이러한 배경에서 공공기술연구회 소속 4개 기관 (항우연, 지질연, 해양연, 건기연)은 2002년 4월 지상분야, 건설분야, 해양분야 등 전문분야별로 원격탐사센터를 설립하여 공공활용 서비스를 위한 국가원격탐사센터로서의 역할을 수행할 수 있도록 협조체계를 구축하였다. 한국건설기술연구원의 건설원격탐사센터에서는 건설 분야와 관련된 지구관측위성 자료의 분석ㆍ활용 및 체계적인 영상 Data Base를 구축하고 이를 Web을 통해 서비스 할 수 있는 체계를 구축하였다. 현재 건설원격탐사센터 홈페이지(http：//krsc.kict.re.kr)는 기 구축된 수자원/하천분야 관련 공간자료를 Web을 통해 서비스하고 있으며 공간자료의 분석을 통해 획득한 연구 성과들을 지속적으로 갱신하고 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.2 no.1 s.2
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• pp.75-84
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• 2003

Current techniques for road-traffic monitoring rely on sensors which have limited capabilities, are costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to current sensors. Video based traffic monitoring systems are now being considered key points of advanced traffic management systems. In this paper, we propose the new method which extract the traffic information using video camera. The proposed method uses an adaptive updating scheme for background in order to reduce the false alarm rate due to various noises in images. also, the proposed extraction method of traffic information calculates the traffic volume ratio of vehicles passing through predefined detection area, which is defined by the length of profile occupied by cars over that of overall detection area. Then the ratio is used to define 8 different states of traffic and to interpret the state of vehicle flows. The proposed method is verified by an experiment using CCTV traffic data from urban area.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.64-72
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• 2007

In this paper we proposed a combined active contour model and motion estimation-based object tracking technique. After assigning the initial contour, we find the object's boundary and update the initial contour by using object's motion information. In the following frames, similar snake algorithm is repeated to make continuously estimated object's region. The snake algerian plays a role in separating the object from background, while motion estimation provides object's moving direction and displacement. The proposed algorithm provides equivalently stable, robust, tracking performance with significantly reduced amount of computation, compared with the existing shape model-based algorithms.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.248-261
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• 2002

In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.111-121
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• 2011

Intelligent video analysis systems require techniques which can predict accidents and provide alarms to the monitoring personnel. In this paper, we present an abnormal behavior analysis technique based on adaptive background generation. More specifically, abnormal behaviors include fence climbing, abandoned objects, fainting persons, and loitering persons. The proposed video analysis system consists of (i) background generation and (ii) abnormal behavior analysis modules. For robust background generation, the proposed system updates static regions by detecting motion changes at each frame. In addition, noise and shadow removal steps are also were added to improve the accuracy of the object detection. The abnormal behavior analysis module extracts object information, such as centroid, silhouette, size, and trajectory. As the result of the behavior analysis function objects' behavior is configured and analyzed based on the a priori specified scenarios, such as fence climbing, abandoning objects, fainting, and loitering. In the experimental results, the proposed system was able to detect the moving object and analyze the abnormal behavior in complex environments.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.98-105
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• 2007

In this paper, we propose the method and system which determines the condition for safe and unsafe lane changing. To determine the condition, first, the system sets up the Region of Interest(ROI) on the neighboring lane. Second, a dangerous vehicle is extracted during the line changing. Third, the condition is determined to wm or not by calculating the moving direction, relative distance md relative velocity. To set up the ROI, the only one side lane is detected and the interested region is expanded. Using the coordinate transformation method, the accuracy of the ROI raised. To correctly extract the vehicle on the neighboring lane, the Adaptive Background Update method and Image Segmentation method which uses the feature of the travelling road are used. The object which is extracted by the dangerous vehicle is calculated the relative distance, the relative velocity and the moving average. And then in order to ring, the direction of the vehicle and the condition for safe and unsafe is determined. As minimizes the interested region and uses the feature of the travelling road, the computational quantity is reduced and the accuracy is raised and a stable result on a travelling road images which demands a high speed calculation is showed.

• Journal of Korea Multimedia Society
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• v.11 no.1
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• pp.34-43
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• 2008

This paper presents a system for recognizing sunglasses and a mask of an ATM (Automatic Teller Machine) user. The proposed system extracts firstly facial contour, then from this extraction results it estimates the regions of eyes and mouth. Finally, it recognizes sunglasses and a mouth using Histogram Indexing based on those regions. We adopt a face shape model to be able to extract facial contour and to estimate the regions of eyes and mouth when those regions are occluded by sunglasses and a mask. To improve the fitting accuracy of the shame model, we adopt 2-step face detection method and conduct fitting several times by varying the initial position of the model instance. To achieve a good performance of the face detection method based on a background model, we enable the system to automatically update the background model. In experiment, we present some experiments on setting parameters of the system with images taken from in our laboratory, and demonstrate the results of recognizing sunglasses and a mask.