• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.182-184
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• 2012

마이크로소프트에서 개발한 키넥트(kinect)는 엑스박스(XBox) 게임 컨트롤러로 사용하는 장비이며 이 센서를 이용하여 사용자의 인체 행동을 인식하여 게임을 진행할 수 있는 센서 시스템이다. 또한 윈도우 환경에서 키넥트를 활용하여 다양한 응용 프로그램 개발을 할 수 있도록 SDK를 제공하고 있다. 현대사회에서 각종 범죄가 늘어남에 따라서 CCTV의 운용이 늘어나고 있으며 지정된 구역을 감시하는데 다양한 영상 장비들과 프로그램이 운용하고 있다. 시장에 판매되고 있는 CCTV 장비들 중에서 사람 추적기능을 가능 제품은 가격이 대부분 고가이다. 또한 야간에서는 사람의 감지가 힘들다. 본 연구에서는 키넥트의 골격 추적기능과 음성인식 기능을 활용하여 실시간 영상 녹화 프로그램을 개발하고자 하며, 개발된 프로그램은 키넥트 센서로 영상을 실시간 녹화하고 침입자에 대한 움직임을 자동 추적하여 녹화하는 DVR 시스템을 제안하고자 한다. 또한 야간에서는 깊이(Depth) 영상을 이용하여 인물을 인식과 추적을 한다. 궁극적으로 키넥트 센서(Kinect Sensor)의 CCTV기능에 대한 활용성을 연구하는데 목적을 가진다.

• Journal of Sensor Science and Technology
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• v.8 no.1
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• pp.69-79
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• 1999

The research and implementation was preformed on high-resolution CCTV camera with CCD exclusive DSP conventional analog signal processor CCTV camera has its limit on auto exposure(AE), auto white balance(AWB), back light compensation(BLC) processing, severe distortion and noise of image, manual control parameter setting, etc. In our study, to resolve the problems in conventional CCTV camera, we made it possible to control AE, AWB, BLC automatically by the use of the DSP, which are used exclusively in the CCD camera produced domestically, and the microcontroller. And we utilized the function of screen display of microcontroller for the user-friendly interface to control CCD camera. And the electronic variable resister(EVR) was used to avoid setting parameters manually in the level of manufacturing process. As the result, It became possible to control parameters of the camera by program. And the cost-down effect was accomplished by improving the reliability of parameter values and reducing the efforts in setting parameters.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.819-834
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• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.391-396
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• 2019

Researches for image processing have been actively progress due to the development of various hardware. For example, in order to prevent various types of crime by a vehicle, there is a method of detecting the location of a criminal vehicle using the existing CCTV in real time. However, certain types of systems and high-performance system requirements make it difficult to apply to existing equipment. In this paper proposes a search algorithm that construct a file database of Korean standard license plate information so that specific vehicles can be quickly searched using existing equipment. In order to evaluate the performance of the file database and the search algorithm proposed in this paper, we set up the search targets at various locations and the results showed that the search algorithm could always check the information by searching the vehicle within a certain time.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.841-846
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• 2010

This paper presents design and implementation of an intelligent video surveillance system. The proposed system has advantages of management efficiency and operation robustness unrelated to working condition compared to conventional CCTV based system. The system hardware is designed and implemented by using commercial chips such as digital media processor and video encoder, video decoder and the functions of software are to analyze temperature distribution of a infrared image and to detect disaster situation such as fire. The required functions are confirmed by testing of the prototype and we verified practicality of the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.404-406
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• 2021

In modern society, artificial intelligence and automation are being applied in various fields due to the development of the 4th industrial revolution and IoT technology. In particular, systems with a high proportion of image processing, such as automated processes, intelligent CCTV, medical industry, robots, and drones, are susceptible to external factors noise. In this paper, we propose a digital filter based on noise estimation and weights to reconstruct an image in a complex noise environment. The proposed algorithm classifies the types of noise using noise judgment, and determines the noise level of the filtering mask to switch the filtering process to obtain the final output. In order to verify the performance of the proposed algorithm, simulation was conducted, compared with the existing filter algorithm, and the results were analyzed.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.915-920
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• 2005

Passenger safety is a primary concern of railway system but, it has been urgent issue that dozens of people are killed every year when they fall off from train platforms. Recently, advancements in IT have enabled applying vision sensors to railway environments, such as CCTV and various camera sensors. The objective of this work is to propose technical and system requirements for establishing intelligent monitoring system using camera equipments in urban transit system. We suppose the system is to determine automatically and in real-time whether anyone or anything is in monitoring area. To achieve the goal, we analyze recent image processing technologies for detection and recognition, and suggest possible direction of system development for applying urban transit system. According to the results, we expect the proposed system requirements will playa key role for establishing highly intelligent monitoring system in railway.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.814-817
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• 2020

The number of single-person households is increasing every year, and there are also high concerns about the crime and safety of single-person households. In particular, crimes targeting women are increasing. Although home surveillance camera applications, which are mostly used by single-person households, only provide intrusion detection functions, this service utilizes AI image recognition technologies such as face recognition and object detection to provide theft, violence, stranger and intrusion detection. Users can receive security-related notifications, relieve their anxiety, and prevent crimes through this service.

• 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.