• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.6
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• pp.507-517
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• 2019

Multi-function radar(MFR) is a system that uses various functions such as detection, tracking, and classification. To operate the functions in real-time, the detection stage in MFR usually uses radar signals for short measurement time. We can utilize several conventional detectors in the MFR system to detect low radar cross section maritime targets in the sea-clutter; however, the detectors, which have been developed to be effective for radar signals measured for a longer time, may be inappropriate for MFR. In this study, we proposed a modelling technique of sea-clutter short measurement time. We combined the modeled sea-clutter signal with the maritime-target signal, which was obtained by the numerical analysis method. Using this combined model, we exploited four independent detectors and analyzed the detection performances.

• Journal of KIISE:Software and Applications
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• v.35 no.12
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• pp.780-788
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• 2008

Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

• Journal of the Korean Institute of Gas
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• v.12 no.2
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• pp.38-41
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• 2008

In this research, we propose a new method for tracking the release rate using the concentration data obtained from the sensor. We used a sensor network that has already been set surrounding the area where hazardous gas releases can occur. From the real-time sensor data, we detected and analyzed releases of harmful materials and their concentrations. Based on the results, the release rate is estimated using the neural network. This model consists of 14 input variables (sensor data, material properties, process information, meteorological conditions) and one output (release rate). The dispersion model then performs the simulation of the expected dispersion consequence by combining the sensor data, GIS data and the diagnostic result of the source term. The result of this study will improve the safety-concerns of residents living next to storage facilities containing hazardous materials by providing the enhanced emergency response plan and monitoring system for toxic gas releases.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.48-58
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• 2003

Recently in order to extinguish the large scale of forest fire efficiently and rapidly the forest fire extinguishment equipment such as helicopters and vehicles has been mobilized. In this situation, the most consideration for the effective extinguishment is to understand the forest fire surrounding area and situation very well and arrange and manage the extinguishment equipment timely. In this paper, the client/serve-based forest fire extinguishment helicopter management system was constructed by integrating GPS(global positioning system) and GIS(geographic information system) technologies. This system manages and considers not only extinguishment equipment information such as helicopters and vehicles including manpower arrangement but also extinguishment environment information such as storing reservoir status and road situation and so on. For this, the real time tracking of helicopter location was first acquired through GPS technology then all the information about forest fire surrounding area was offered through the user-friendly interface of GIS concept. The result of constructing this system helps to extinguish a large scale of forest fire rapidly and effectively within shorter time then reduces physical damage and much manpower mobilization.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.29-37
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• 2024

In this paper, we propose an efficient image processing system to detect and track the movement of specific objects such as patients. The proposed system extracts the outline area of an object from a binarized difference image by applying a thinning algorithm that enables more precise detection compared to previous algorithms and is advantageous for mixed-mode design. The binarization and thinning steps, which require a lot of computation, are designed based on RTL (Register Transfer Level) and replaced with optimized hardware blocks through logic circuit synthesis. The designed binarization and thinning block was synthesized into a logic circuit using the standard 180n CMOS library and its operation was verified through simulation. To compare software-based performance, performance analysis of binary and thinning operations was also performed by applying sample images with 640 × 360 resolution in a 32-bit FPGA embedded system environment. As a result of verification, it was confirmed that the mixed-mode design can improve the processing speed by 93.8% in the binary and thinning stages compared to the previous software-only processing speed. The proposed mixed-mode system for object recognition is expected to be able to efficiently monitor patient movements even in an edge computing environment where artificial intelligence networks are not applied.

• Journal of the Korea Society of Computer and Information
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• v.25 no.1
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• pp.101-107
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• 2020

We propose a realistic seeing through visualization methods in mixed reality environment. When a user wants to see specific location beyond a wall in indoor environment. The proposed system recognizes and registers the selected area using environment modelling and feature-based tracking. Then the selected area is diminished and the specific location is visualized in real-time. With the proposed seeing through methods, a user can understand spatial relationship of the building and can easily find the target location. We conducted a user study comparing the seeing through method to conventional indoor navigation service in order to investigate the potential of the proposed seeing through method. The proposed seeing through method was evaluated in navigation time in comparison with conventional approach. The proposed method enable users to navigate target locations 30% faster than the conventional approach.

• Journal of the Korea Computer Graphics Society
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• v.23 no.5
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• pp.67-73
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• 2017

We propose several techniques which can be employed in a 3D fitness program for monitoring and correcting user's posture. To implement a 3D fitness program, improved reference motion generating techniques and visualizing techniques are necessary. First, in order to understand the difference between the user and the reference movement of a professional, a retargeting method between two different body shapes are studied. Second, the problem of self-occlusion, which occurs when using a low-cost depth sensor to represent complex motions, is solved by using a sample database and time consistency. The system proposed in this paper evaluates the user's posture considering the physical characteristics of the user, and then provides feedback to the user.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.73-79
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• 2014

In this paper, we proposed the mechanism which can measure traffic flow and vehicle speed on the highway as well as road by using the video and image processing to detect and track cars in a video sequence. The proposed mechanism uses the first few frames of the video stream to estimate the background image. The visual tracking system is a simple algorithm based on the sum of absolute frame difference. It subtracts the background from each video frame to produce foreground images. By thresholding and performing morphological closing on each foreground image, the proposed mechanism produces binary feature images, which are shown in the threshold window. By measuring the distance between the "first white line" mark and the "second white line"mark proceeding, it is possible to find the car's position. Average velocity is defined as the change in position of an object divided by the time over which the change takes place. The results of proposed mechanism agree well with the measured data, and view the results in real time.

• Journal of the Korea Society of Computer and Information
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• v.12 no.4
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• pp.69-75
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• 2007

On the wireless communication between RFID Tag and Reader, there are some existing problems with weaknesses of security such as spoofing, replay, traffic analysis, position tracking, etc., in the established hash lock related algorithm. This paper has presented the comparison and analysis of the established hash lock related algorithm for privacy and in order to make up for this, also suggested a new security authentication algorithm based on hash which has an authentication protocol and creates hash function by using random numbers received from the reader on real time and every session. The algorithm suggested here can offer a several of usefulness for RFID authentication system and it has an advantage to reduce the amount of calculations compared to established algorithm. It also uses the tags needed among a lot of tags around which are expected later and it is expected to reduce a responsibility of the server by ending unnecessary tags' operation with time based.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.203-208
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• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.