• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.200-202
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• 2004

This paper deals with the real-time monitoring and control system using PC, PDA(Win CE embedded device) and PCS(based BREW platform). The camera attached to the server captures the moving target, and the captured frame of color image is encoded in JPEG for image compression at the server. The client(PC, PDA, PCS) receives the image data from the remote server and the received image is decoded from decompression. We use the TCP/IP protocol to send the image frames. The client can control the position of the camera by sending the control command to the server. Two DC servo motors for the camera are controlled in any directions, up-down and left-right, by the controller which is communicating with the server via the serial communication to get the control command. In this way, on the client we can monitor the moving images at the server and also control the position of the camera.

• Journal of Biosystems Engineering
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• v.24 no.5
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• pp.439-444
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• 1999

Automated greenhouse production systems often require crop growth monitoring involving accurate quantification of plant physiological properties. Conventional methods are usually burdensome, inaccurate, and harmful to crops. A thermal image analysis system can accomplish rapid and accurate measurements of physiological-property changes of stressed crops. In this research a thermal imaging system was used to measure the leaf-temperature changes of several crops according to water deficit. Thermal images were obtained from lettuce, cucumber, pepper, and chinese cabbage plants. Results showed that there were significant differences in the temperature of stressed plants and non-stressed plants. The temperature differences between these two group of plants were 0.7 to 3$^{\circ}C$ according to species.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.243-243
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• 2000

This paper introduces a visual inspecting and monitoring system based on an image processing technique. We propose an image processing method for analyzing landslide movement in real time. The method adopts Laplacian of Gaussian operator to extract linear features for the captured images and uses a linear matching algorithm to distinguish the matching error for those features. When the algorithm is processed, motion parameters such as displacement area and its direction are computed. Once movement is recognized, displacements are estimated graphically with statistical amount in the image plane. The simulation results are shown us to verify the effectiveness of the developed method.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.11a
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• pp.261-262
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• 2023

Drone is a suitable equipment for capturing images of cracks at construction sites based on its efficient mobility and high-resolution image acquisition capabilities. In this study, drone was used to acquire indoor construction sites framework images and deep learning technology was applied to detect cracks and measure width, and size. Finally, the usability of the process was verified based on the indoor crack monitoring system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1597-1610
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• 2022

At present, the main method of high-speed train chassis detection is using computer vision technology to extract keypoints from two related chassis images firstly, then matching these keypoints to find the pixel-level correspondence between these two images, finally, detection and other steps are performed. The quality and accuracy of image matching are very important for subsequent defect detection. Current traditional matching methods are difficult to meet the actual requirements for the generalization of complex scenes such as weather, illumination, and seasonal changes. Therefore, it is of great significance to study the high-speed train image matching method based on deep learning. This paper establishes a high-speed train chassis image matching dataset, including random perspective changes and optical distortion, to simulate the changes in the actual working environment of the high-speed rail system as much as possible. This work designs a convolutional neural network to intensively extract keypoints, so as to alleviate the problems of current methods. With multi-level features, on the one hand, the network restores low-level details, thereby improving the localization accuracy of keypoints, on the other hand, the network can generate robust keypoint descriptors. Detailed experiments show the huge improvement of the proposed network over traditional methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.56-62
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• 2004

This research attempts to suggest a detecting method for cutting position of an object using the neural network, which is one of intellectual methods, and the digital image processing method. The extraction method of object information using the image data obtained from the CCD camera as a replacement of traditional analog sensor thanks to the development of digital image processing. Accordingly, this research determines the threshold value in binary-coding of an input image with the help of image processing method and the neural network for the real-time gray-leveled input image in substitution for lighting; as a result, a specific position is detected from the processed binary-coded image and an actual system designed is suggested as an example.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11S
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• pp.3243-3250
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• 1999

There are many problems to be satisfied the various commercial demand in the present VRML node, and the VRML-based system by the contact with other technology is burdened with the direct participation of developer related with it. In this study, remote control and monitoring system using EAI(External Authoring Interface) is reposed to overcome the limit of VRML. In other words, This study is about mechanism of interaction between control and monitoring subject in real world and object in virtual world mapped with it. Object oriented method by one to one mapping of the Java class which have VRML virtual world and the object control is proposed. Introduction method of video monitoring through method of image synthesis and the integrated development environment is described. Finally automobile-gate control system based on the development method of Internet virtual reality-based system which is proposed in this study is described.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.507-515
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• 2002

Remote Sensing Monitoring and Loss Estimated System of Flood Disaster based on GIS is an integrated system comprised flood disaster information receiving and collection, flood disaster simulation, and flood disaster estimation. When the system receives and collects remote sensing monitoring and conventional investigation information, the distributional features of flood disaster on space and time is obtained by means of image processing and information fusion. The economic loss of flood disaster can be classified into two pus: direct economic loss and indirect economic loss. The estimation of direct economic loss applies macroscopic economic analysis methods, i.e. applying Product (Industry and Agriculture Gross Product or Gross Domestic Product - GDP) or Unit Synthetic Economic Loss Index, direct economic loss can be estimated. Estimating indirect economic loss applies reduction coefficient methods with direct economic loss. The system can real-timely ascertains flood disaster and estimates flood Loss, so that the science basis fur decision-making of flood control and relieving disaster may be provided.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.4
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• pp.637-645
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• 2022

Cloud computing has been gaining popularity over decades, and container, a technology that is primarily used in cloud native applications, is also drawing attention. Although container technologies are lighter and more capable than conventional VMs, there are several security threats, such as sharing kernels with host systems or uploading/downloading images from the image registry. one of which can refer to the integrity of container images. In addition, runtime security while the container application is running is very important, and monitoring the behavior of the container application at runtime can help detect abnormal behavior occurring in the container. Therefore, in this paper, first, we implement a signing checker that automatically checks the signature of an image based on the existing Docker Content Trust (DCT) technology to ensure the integrity of the container image. Next, based on falco, an open source project of Cloud Native Computing Foundation(CNCF), we introduce newly created image for the convenience of existing falco image, and propose implementation of docker-compose and package configuration that easily builds a monitoring system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.1
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• pp.206-213
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• 2007

In this paper, The monitoring system for TV advertisement is implemented using video watermark. The functions of the advertisement monitoring system are monitoring the time, length, and index of the on-air advertisement, saving the log data, and reporting the monitoring result. The performance of the video watermark used in this paper is tested for TV advertisement monitoring. This test includes LAB test and field test. LAB test is done in laboratory environment and field test in actually broadcasting environment. LAB test includes PSNR, distortion measure in image, and the watermark detection rate in the various attack environment such as AD/DA(analog to digital and digital to analog) conversion, noise addition, and MPEG compression. The result of LAB test is good for the TV advertisement monitoring. KOBACO and SBS are participated in the field test. The watermark detection rate is 100% in both the real-time processing and the saved the processing. The average deviation of the watermark detection time is 0.2 second, which is good because the permissible average error is 0.5 second.