• Journal of Digital Contents Society
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• v.14 no.4
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• pp.447-454
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• 2013

As the surveillance CCTVs are increasing every year, big data image processing for the CCTV image data has become a hot issue. In this paper, we propose a Hadoop-based big data image processing technique to recognize a vehicle number from a large amount of automatic number plate images taken from CCTVs. We also implement the vehicle route tracking system that displays the moving path of the searched vehicle on Google Maps with the related information together. In order to evaluate the performance we compare and analysis the vehicle number recognition time for a lot of CCTV image data in Hadoop and the single PC environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.108-115
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• 2013

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. In this field, area for technique can be divided into Foreground Subtraction which detects individuals and objects in a potential observing area and a tracing technology which figures out moving route of individuals and objects. In this thesis, an improved algorism for a settled engine development, which is stable to change in both noise and illumination for detecting moving objects is suggested. The proposed algorism from this thesis is focused on designing a stable and real time processing method which is perfect model in detecting individuals, animals, and also low-speeding transports and catching a change in an illumination and noise.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.4
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• pp.153-160
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• 2016

A developed skill of an intelligent CCTV is also advancing by using its Image Acquisition Device. The most important part in the field of detecting comparatively fast moving objects is to effectively reduce the loads on updating the background image in order to achieve real-time update. However, the ability of the current general-purpose computer extracting the texture as characteristics has limits in application mostly due to the loads on processes. In this thesis, an algorithm for real-time updating the background image in an applied area such as detecting the fast moving objects like a driving car in a video of at least 30 frames per second is suggested and the performance is analyzed by a test of extracting object region from real input image.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.105-106
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• 2014

본 논문에서는 통행 시간의 측정 방법 중 하나인 CCTV를 활용한 주행 차량 조사법을 이용하여 교통량을 측정한다. 교통망의 서비스 수준을 측정하는 주요 기준인 통행 시간과 지체 시간에 대하여 알아본다. 신호등 간격이 넓어서 연속적인 교통류 특성을 갖는 곳에서 측정을 하도록 한다. 반대편의 교통류가 충분히 식별 가능한 구간이어야 하고, 구간의 끝부분에서는 유턴이 가능해야 한다. 이 방법은 측정차량의 운전수만 있으면 CCTV와 프로그램이 알아서 측정하고, 시간, 거리, 교통량을 기록할 수 있는 장비도 필요 없다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.15-25
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• 2014

In this paper, we propose a loitering detection using trajectory probability distribution and local direction descriptor for intelligent surveillance system. We use a background modeling method for detecting moving object and extract the motion features from each moving object for making feature vectors. After that, we detect the loitering behavior person using K-Nearest Neighbor classifier. We test the proposed method in real world environment and it can achieve real time and robust detection results.

• Journal of Industrial Convergence
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• v.18 no.3
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• pp.53-61
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• 2020

Travel speed is an important parameter for measuring road traffic and incident detection system. In this paper I suggests a model developed for estimating reliable and accurate average roadway link travel speeds using image processing sensor. This method extracts the vehicles from the video image from CCTV, tracks the moving vehicles using deep neural network, and extracts traffic information such as link travel speeds and volume. The algorithm estimates link travel speeds using a robust data-fusion procedure to provide accurate link travel speeds and traffic information to the public. In the field tests, the new model performed better than existing methods.

• Journal of Satellite, Information and Communications
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• v.11 no.1
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• pp.55-57
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• 2016

In this paper, we present an algorithm to determine the abnormal behavior through a CCTV-based behavioral recognition and a pattern of hand using ConvexHull. In the existing way that using CCTV for crime prevention, facial recognition is mainly used. Facial recognition is the way that compares the faces that are seen on the screen and faces of criminals for determining how dangerous targets are, however, this way is hard to predict future criminal behavior. Therefore, to predict more various situations, abnormal behaviours are determined with targets' incline of arms, legs and bodys and patterns of hand movements. it can forecast crimes when an acting has been getting within common normality out, comparing whose acting patterns with the crime patterns.

• Smart Media Journal
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• v.1 no.3
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• pp.43-47
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• 2012

The recent proliferation of multimedia data necessitates the effectively and efficiently retrieving of multimedia data. These research not only focus on the retrieving methods of text matching but also on using the multimedia data features. Therefore, this paper is a similarity measurement method of trajectory using indexing information of moving object in video, for similarity measurement. This method consists of 2 steps. Firstly, Video data is processed indexing for trajectory extraction of moving objects using CCTV. Finally, we describe to compare DTW(Dynamic Time Warping) to TSR(Tansent Space Representation) algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.6
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• pp.36-45
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• 2009

Recently, there are interested in the automatic traffic flowing and accident detection using various low level information from video in the road. In this paper, the automatic traffic flowing and algorithm, and application of traffic accident detection using traffic management systems are studied. To achieve these purposes, the spatio-temporal relation models using topological and directional relations have been made, then a matching of the proposed models with the directional motion verbs proposed by Levin's verbs of inherently directed motion is applied. Finally, the synonym and antonym are inserted by using WordNet. For the similarity measuring between proposed modeling and trajectory of moving object in the video, the objects are extracted, and then compared with the trajectories of moving objects by the proposed modeling. Because of the different features with each proposed modeling, the rules that have been generated will be applied to the similarity measurement by TSR (Tangent Space Representation). Through this research, we can extend our results to the automatic accident detection of vehicle using CCTV.