• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.9
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• pp.1035-1042
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• 2014

Object recognition is one of the key technologies of the monitoring system for the prevention of various intelligent crimes. The height is one of the physical information of a person, and it may be important information for identification of the person. In this paper, a method which can detect pedestrians from CCTV images and estimate the height of the detected objects, is proposed. In this method, GMM (Gaussian Mixture Model) method was used to separate the moving object from the background and the pedestrian was detected using the conditions such as the width-height ratio and the size of the candidate objects. The proposed method was applied to the CCTV video, and the height of the pedestrian at far-distance, middle- distance, near-distance was estimated for the same person, and the accuracy was evaluated. Experimental results showed that the proposed method can estimate the height of the pedestrian as the accuracy of 97% for the short-range, 98% for the medium-range, and more than 97% for the far-range. The image sizes for the same pedestrian are different as the position of him in the image, it is shown that the proposed algorithm can estimate the height of pedestrian for various position effectively.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.4
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• pp.309-315
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• 2018

Currently, the commercialization of the $5^{th}$ Generation (5G) service is becoming more prevalent in domestic communication network technology. This has reduced communication delay time and enabled large-capacity data transmission and video streaming services in real-time. In order to keep pace with these developments, K-water has introduced a smart process control system in water purification plants to monitor the status of the water purification process. However, since wireless networks are based on the public Long Term Evolution (LTE) network, communication delay time remains high, and high-resolution video services are limited. This is because communication networks still have a closed structure due to expense and security issues. Therefore, with 5G in its current form, it is very difficult to accommodate future services without improving the infrastructure of its communication networks. In recognition of these problems, this study implemented the authentication and management function of wireless networks on a wired network management system in the K-water Bansong water purification plant. The results confirmed that wired Local Area Network (LAN) services give a higher security performance than an expensive commercial wireless LAN system. This was achieved by using an Internet Protocol (IP) address management system of wired networks and the packet filtering function of the Layer2 (L2) switch. This study also confirmed that it is possible to create a wireless LAN service that is 3.7 times faster than the existing LTE communication network.

• The Journal of the Korea Contents Association
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• v.12 no.9
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• pp.40-47
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• 2012

Existing art, media art, accompanied by a new path of awareness and perception instrumentalized by the human body, creating a new way to watch the interaction is proposed. Western art way to create visual images of the point cloud that represented a form that is similar to the Pointage. This traditional painting techniques using digital technology means reconfiguration. In this paper, a new appreciation of fusion of aesthetic elements and digital technology, making the point cloud in the form of video. And this holographic film projection of the spectator, and gestures to interact with the video content is presented. A Process of making contents is intent planning, content creation, content production point cloud in the form of image, 3D gestures for interaction design process, go through the process of holographic film projection. Visual and experiential content of memory recall process takes place in the consciousness of the people expressed. Complete the process of memory recall, uncertain memories, memories materialized, recalled. Uncertain remember the vague shapes of the point cloud in the form of an image represented by the image. As embodied memories through the act of interaction to manipulate images recall is complete.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.12
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• pp.2982-2988
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• 2014

The edge detection is a pre-processing of such as image segmentation, image recognition, etc, and many related studies are being conducted both in domestic and abroad. Representative edge detection methods are Sobel, Prewitt, Laplacian, Roberts and Canny edge detectors. Such existing methods are possible for superb detections of edges if edges are detected from videos without noises. However, for video degraded by the salt-and-pepper noise, the edge detection characteristic is shown to be insufficient due to the noise influence. Therefore, in this study, the area is separated as the top, down, left and right from the mask's center pixel first to acquire a superb edge detection characteristic from the video damaged by the salt-and-pepper noise. And the algorithm that detects the final edge by applying the directional mask on the assumed factor of mask that is obtained according to the result of determination for the noise status of representative pixel value of each area.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.77-83
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• 2020

Recently, intelligent predictive surveillance system has emerged. It is a system that can probabilistically predict the future situation and event based on the existing data beyond the scope of the current object or object motion and situation recognition. Since such intelligent predictive monitoring system has a high possibility of handling personal information, security consideration is essential for protecting personal information. The existing video surveillance framework has limitations in terms of privacy. In this paper, we proposed a security framework for intelligent predictive surveillance system. In the proposed method, detailed components for each unit are specified by dividing them into terminals, transmission, monitoring, and monitoring layers. In particular, it supports active personal information protection in the video surveillance process by supporting detailed access control and de-identification.

• Journal of Korean Elementary Science Education
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• v.23 no.1
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• pp.50-60
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• 2004

The purpose of this study was to define teachers' learning motivation strategies and students' responses by analyzing science classes and interviews. The subjects were first grade and sixth grade teachers and students of an elementary school. The analysis tools are based on Keller's ARCS theory. The differences of teachers' motivation strategies were analyzed by grades and teachers' and students' backgrounds. The interviewers were composed of three teachers and three students of first grade, and three teachers and three students of sixth grade. The data were collected by recording of the classes using tape recorders, video cameras, and notebooks written by researchers. The results are as follows. First, teachers had their own styles of teaching strategies in their classes. Especially teachers' teaching backgrounds affected on the teachers' instructional strategies. The teachers who had long teaching experiences of lower grade students used to show a lot of attention strategies. While the teachers with long teaching experiences of higher grade students used to show few learning motivation strategies. Especially, sixth grade teachers used to show fewer confidence strategies than first grade teachers. Second, all of the teachers used to show few satisfaction strategies commonly in all the classes observed. Third, the students' recognition of the motivation strategies were not different according to their conceptions or activities of the classes. Commonly first grade students focused on the attention strategies, while sixth grade students focused on negative motivation strategies. Fourth, the teachers who believed that students need detail guidance and control recognized the needs of satisfaction strategies by students' autonomous activities after observing video tapes of other teachers' classes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1183-1189
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• 2021

There have been recently an increasing number of people working out at home. However, many of them do not have face-to-face guidance from experts, so they cannot effectively correct their wrong pose. This may lead to strain and injury to those doing home training. To tackle this problem, this paper proposes a video data-based pose classification and correction system for home training. The proposed system classifies poses using the multi-layer perceptron and pose estimation model, and corrects poses based on joint angels estimated. A voting algorithm that considers the results of successive frames is applied to improve the performance of the pose classification model. Multi-layer perceptron model for post classification shows the highest accuracy with 0.9. In addition, it is shown that the proposed voting algorithm improves the accuracy to 0.93.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.44-49
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• 2021

Recently, due to COVID-19, studies have been popularly worked to apply neural network to mask wearing automatic detection system. For applying neural networks, the 1-stage detection or 2-stage detection methods are used, and if data are not sufficiently collected, the pretrained neural network models are studied by applying fine-tuning techniques. In this paper, the system is consisted of 2-stage detection method that contain MTCNN model for face recognition and ResNet model for mask detection. The mask detector was experimented by applying five ResNet models to improve accuracy and fps in various environments. Training data used 17,217 images that collected using web crawler, and for inference, we used 1,913 images and two one-minute videos respectively. The experiment showed a high accuracy of 96.39% for images and 92.98% for video, and the speed of inference for video was 10.78fps.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.17-22
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• 2022

In this paper, we design a lightweight embedded device that can support intelligent edge computing, and show that the device quickly detects an object in an image input from a camera device in real time. The proposed system can be applied to environments without pre-installed infrastructure, such as an intelligent video control system for industrial sites or military areas, or video security systems mounted on autonomous vehicles such as drones. The On-Device AI(Artificial intelligence) technology is increasingly required for the widespread application of intelligent vision recognition systems. Computing offloading from an image data acquisition device to a nearby edge device enables fast service with less network and system resources than AI services performed in the cloud. In addition, it is expected to be safely applied to various industries as it can reduce the attack surface vulnerable to various hacking attacks and minimize the disclosure of sensitive data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.675-681
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.