• Journal of the Korean institute of surface engineering
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• v.54 no.5
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• pp.278-284
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• 2021

Corrosion of steel plate is common phenomenon which results in the gradual destruction caused by a wide variety of environments. Corrosion monitoring is the tracking of the degradation progress for a long period of time. Corrosion on steel plate appears as a discoloration and any irregularities on the surface. In this study, we developed a quantitative evaluation method of the rust formed on steel plate by using k-means clustering from the corroded area in a given image. The k-means clustering for automated corrosion detection was based on the GrabCut segmentation and Gaussian mixture model(GMM). Image color of the corroded surface at cut-edge area was analyzed quantitatively based on HSV(Hue, Saturation, Value) color space.

• ETRI Journal
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• v.43 no.3
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• pp.459-470
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• 2021

This paper presents a low-cost prototype for monitoring online the maximum power produced by a domestic photovoltaic (PV) system using Internet of Things (IoT) technology. The most common tracking algorithms (P&O, InCond, HC, VSS InCond, and FL) were first simulated using MATLAB/Simulink and then implemented in a low-cost microcontroller (Arduino). The current, voltage, load current, load voltage, power at the maximum power point, duty cycle, module temperature, and in-plane solar irradiance are monitored. Using IoT technology, users can check in real time the change in power produced by their installation anywhere and anytime without additional effort or cost. The designed prototype is suitable for domestic PV applications, particularly at remote sites. It can also help users check online whether any abnormality has happened in their system based simply on the variation in the produced maximum power. Experimental results show that the system performs well. Moreover, the prototype is easy to implement, low in cost, saves time, and minimizes human effort. The developed monitoring system could be extended by integrating fault detection and diagnosis algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.320-322
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• 2021

With the development of wireless Internet technology and the expansion of the game market, various forms of games are being developed that are mounted on various platforms, including mobile platforms. In this environment, ensuring the immersion of the game user's perspective will secure the game's competitiveness, so it is necessary to increase the immersion by satisfying each area presented by the Human Computer Interaction (HCI) theory. To this end, this high school implemented downhill games and experimented with kiosks by applying an interface that recognizes the human body's movements as a way to secure freedom and immersion of game users.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1435-1447
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• 2015

Finance Companies are operating a security solution such as E-DRM(Enterprise-Digital Right Management), Personal information search, DLP(Data Loss Prevention), Security of printed paper, Internet network separation system, Privacy monitoring system for privacy leakage prevention by insiders. However, privacy leakages are occurring continuously and it is difficult to the association analysis about relating to the company's internal and external distribution of private document. Because log system operated in the separate and independent security solutions. This paper propose a systematic chains that can correlatively analyze business systems and log among heterogeneous security solutions organically and consistently based on security documents. Also, we suggest methods of efficient detection for Life-Cycle management plan about security documents that are created in the personal computer or by individual through the business system and distribution channel tracking about security documents contained privacy.

• Journal of Sensor Science and Technology
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• v.11 no.5
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• pp.255-262
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• 2002

Human retina is able to detect the edge of an object effectively. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge detection. There are several fluctuation factors which affect characteristics of MOSFETs during CMOS fabrication process and this effect appears as output offset of the vision chip which is composed of pixel arrays and readout circuits. The vision chip detecting edge information from input image is used for input stage of other systems. Therefore, the output offset of a vision chip determine the efficiency of the entire performance of a system. In order to eliminate the offset at the output stage, we designed a vision chip by using CDS(Correlated Double Sampling) technique. Using standard CMOS process, it is possible to integrate with other circuits. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.160-166
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• 2020

As mobile-based hardware technology develops, many kinds of applications are also being developed. In addition, there is an increasing demand to automatically check that the interface of these applications works correctly. In this paper, we describe a method for accurately detecting faulty images from applications by comparing major characteristics from input color images. For this purpose, our method first extracts major characteristics of the input image, then calculates the differences in the extracted major features, and decides if the test image is a normal image or a faulty image dissimilar to the reference image. Experiment results show that the suggested approach robustly determines similar and dissimilar images by comparing major characteristics from input color images. The suggested method is expected to be useful in many real application areas related to computer vision, like video indexing, object detection and tracking, image surveillance, and so on.

• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.323-335
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• 2012

In this paper, we propose an AR(augmented reality) system using user's bare hand based on computer vision. It is important for registering a virtual object on the real input image to detect and track correct feature points. The AR systems with markers are stable but they can not register the virtual object on an acquired image when the marker goes out of a range of the camera. There is a tendency to give users inconvenient environment which is limited to control a virtual object. On the other hand, our system detects fingertips as fiducial features using adaptive ellipse fitting method considering the geometric characteristics of hand. It registers the virtual object stably by getting movement of fingertips with determining the shortest distance from a palm center. We verified that the accuracy of fingertip detection over 82.0% and fingertip ordering and tracking have just 1.8% and 2.0% errors for each step. We proved that this system can replace the marker system by tacking a camera projection matrix effectively in the view of stable augmentation of virtual object.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.19-27
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• 2020

In this study, Developing high resolution camera and Social Network Service sharing image can be easily getting images, it cause about taking fingerprints to easy from images. So I present solution about prevent to taking fingerprints. this technology is develop python using to opencv, blur libraries. First of all 'Hand Key point Detection' algorithm is used to locate the hand in the image. Using this algorithm can be find finger joints that can be protected while minimizing damage in the original image by using the coordinates of separate blurring the area of fingerprints in the image. from now on the development of accurate finger tracking algorithms, fingerprints will be protected by using technology as an internal option for smartphone camera apps from high resolution images.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.1
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• pp.94-98
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• 2015

Recently, with the rapid advancement in information and computer vision technology, a CCTV system using object recognition and tracking has been studied in a variety of fields. However, it is difficult to recognize a precise object outdoors due to varying pixel values by moving background elements such as shadows, lighting change, and moving elements of the scene. In order to adapt the background outdoors, this paper presents to analyze a variety of background models and proposed background update algorithms based on the weight factor. The experimental results show that the accuracy of object detection is maintained, and the number of misrecognized objects are reduced compared to previous study by using the proposed algorithm.