• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.9
• /
• pp.1082-1087
• /
• 2019

Video Incident Detection System is a detection system for the purpose of detection of an emergency in an unexpected situation such as a pedestrian in a tunnel, a falling object, a stationary vehicle, a reverse run, and a fire(smoke and flame). In recent years, the importance of the city center has been emphasized by the construction of underpasses in great depth underground space. Therefore, in order to apply Video Incident Detection System to a Double Deck Tunnel, it was developed to reflect the design characteristics of the Double Deck Tunnel. and In this paper especially, the fire detection technology, which is not it is difficult to apply to the Double Deck Tunnel environment because it is not supported on existing Video Incident Detection System or has a fail detect, we propose fire detection using color image analysis, silhouette spread, and statistical properties, It is verified through a real fire test in a double deck tunnel test bed environment.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.400-402
• /
• 2019

The electric point machine, which is used for the control of the turnout used to change the track of the train, is very important in the railway system. Various wired and wireless real-time monitoring systems are used to check the status of the point machine, but there is a possibility of malfunction due to sensor or network error. In this paper, a redundant monitoring system was designed that incorporates the point machine monitoring system and the CCTV camera control system to double check the operation of the point machine. In the point machine monitoring system, the operating state of the railway converter is monitored, alarmed and transmitted over the network. The CCTV camera control system, which received this information, was required to record the status of the turnout and the point machine in question and send it to the administrator. The manager of the railway line can check the conversion status of the railway through the monitoring screen for the railway line switcher first, and then confirm the switching status directly through the CCTV camera image, thereby improving the reliability of the point machine operation. It will also enable the safe and efficient operation of personnel for management. It is expected to contribute to preventing a derailment caused by a malfunction of the point machine.

• Journal of Korea Entertainment Industry Association
• /
• v.15 no.8
• /
• pp.107-116
• /
• 2021

In recent years, the research on audience satisfaction after watching programs has been carried out in various fields. However, there is no precedent for the study of simply analyzing the influencing factors of audience satisfaction with the newly established CCTV-9 channel. For CCTV-9, how to explore the strategy of industrial development based on the needs of the audience in the era of big data is a very important part. This article exploratively focuses on the influencing factors related to CCTV-9 audience satisfaction. Using questionnaires, 101 samples of the satisfaction with the channel of men and women of different ages, education backgrounds, majors, and incomes were collected to test, and 9 hypotheses were tentatively proposed as relevant influencing factors of channel satisfaction. Through empirical analysis, this research searches for the determinants. The reliability and validity of the measurement were properly analyzed, and all hypotheses were statistically tested. The empirical results show that: subject matter, program format, program scheduling, program broadcast time, channel advertising, simulcast series of documentaries, diversified communication platforms, brand image packaging and audience satisfaction are significantly positively correlated.

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

• Journal of Digital Convergence
• /
• v.14 no.11
• /
• pp.143-148
• /
• 2016

There is increasing concern about security as a need for increased safety in the information industry society. However, it does not meet the needs for safety including CCTV. Therefore, in this paper, we link the processing technology using the image information to the IPS system consisting of GPS and Beacon. It designed a conventional RFID tag attached discomfort and image tracking system is limited to complement the disadvantages identifiable area. To this end, we designed a smart device and the Internet of Things convergence system and a research to ensure the accuracy and reliability of the IPS of the access control system. Finally, by leveraging intelligent video information using a PTZ camera, and set the entrant management policies it was carried out to control the situation and control. Also, by designing the integrated video tracking system, an authentication server, visualization systems were designed to establish an efficient technique for analyzing the IPS entrant behavior patterns.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.26 no.4
• /
• pp.259-266
• /
• 2016

Recently, CCTV cameras are emplaced actively to reinforce security and intelligent surveillance systems have been under development for detecting and monitoring of the objects in the video. In this study, we propose a method for detection of upper body in intelligent surveillance system using FCM-based RBFNN classifier realized with the aid of HOG features. Firstly, HOG features that have been originally proposed to detect the pedestrian are adopted to train the unique gradient features about upper body. However, HOG features typically exhibit a very high dimension of which is proportional to the size of the input image, it is necessary to reduce the dimension of inputs of the RBFNN classifier. Thus the well-known PCA algorithm is applied prior to the RBFNN classification step. In the computer simulation experiments, the RBFNN classifier was trained using pre-classified upper body images and non-person images and then the performance of the proposed classifier for upper body detection is evaluated by using test images and video sequences.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.6
• /
• pp.819-824
• /
• 2021

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.210-212
• /
• 2021

In modern society, various digital equipment are being distributed due to the influence of the 4th industrial revolution, and they are used in a wide range of fields such as automated processes, intelligent CCTV, medical industry, robots, and drones. Accordingly, the importance of the preprocessing process in a system operating based on an image is increasing, and an algorithm for effectively reconstructing an image is drawing attention. In this paper, we propose a filter algorithm based on a combined weight value to reconstruct an image in a complex noise environment. The proposed algorithm calculates the weight according to the spatial distance and the weight according to the difference between the pixel values for the input image and the pixel values inside the filtering mask, respectively. The final output was filtered by applying the join weights calculated based on the two weights to the mask. In order to verify the performance of the proposed algorithm, we simulated it by comparing it with the existing filter algorithm.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.07a
• /
• pp.75-76
• /
• 2020

본 논문에서는 스마트 폰 등의 영상수신장치들이 원격으로 접속하여 다양한 인터페이스를 갖는 영상취득 장치들 중 하나를 선택하여 제어하면서 해당 영상을 수신할 수 있는 영상송신시스템을 제안한다. 제안하는 영상송신시스템은 우선적으로 야간의 물리적 보안을 위한 영상취득용 초저도 카메라를 위해 고정된 4개의 컴포지트 및 USB CAM 활용을 위한 인터페이스들 및 이를 위한 해당 기능들, 영상수신장치들이 무선으로 접속하여 채널을 확보하기 위한 Soft-AP 기능, 접속된 영상수신장치들에게 해당 영상을 전송하며 이렇게 연결된 다수의 장치를 제어하는 등의 전반적인 관리를 위한 기능 등으로 구성되는데, 이러한 기능들의 소프트웨어적 구현에 비중을 두어 기술한다.