• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.564-567
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• 2005

For the application of monitoring system of the machine tool to industry, the requirements such as high reliability and low cost need to be satisfied. In this study, a reliable but inexpensive monitoring method for machine tool is introduced. To improve the monitoring reliability, several kinds of information related to machining and operation are selected; real-time video clip from USB camera, operation data and signal from CNC and feed motor torque. Especially, to improve the quality of real-time video clip, a camera housing is developed, it can significantly reduce the vibration effect and prevent from coolant and chip. The collected information are transferred to the monitoring terminals in remote sites using OPC and TCP/IP protocol over Ethernet, which give us convenience of development and interoperability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.51-57
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• 2006

This study is concerned with image information management system for small scale hospital. We intended to developing image management system which is used of the existing analog devices such as medical camera, supersonic analyser, endoscope etc. We developed a video in interface board based USB 2.0 for handling image in real time. It is capable of transmitting image input signal like as NTSC, PAL to personal computer through USB 2.0. The developed the board of 40 speeds compared with the exiting system based USB 1.0. Especially the developed system is very helpful for small hospital like as dental clinic, because it is easy and convenient to manage image information without expert. So it will provide reduction of time and cost for handling image information(collecting, saving, retrieval, transmitting image).

• Journal of Industrial Technology
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• v.29 no.A
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• pp.47-54
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• 2009

In this paper, we proposed hand detection and hand gesture recognition from USB camera video. Firstly, we extract hand region extraction using skin color information from a difference images. Background image is initially stored and extracted from the input images in order to reduce problems from complex backgrounds. After that, 16-directional chain code sequence is computed from the tracking of hand motion. These chain code sequences are compared with pre-trained models using DP matching. Our hand gesture recognition system can be used to control PowerPoint slides or applied to multimedia education systems. We got 92% hand region extraction accuracy and 82.5% gesture recognition accuracy, respectively.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.21-26
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• 2017

In this paper, an USB-OTG (Uiversal Serial Bus On-the-go) interface module was designed with the iris information for personal identification. The image recognition algorithm which was searching face and iris areas, was proposed with pixel differences from eye blinking after several facial images were captured and then detected without any activities like as pressing the button of smart phone. The region of pupil and iris could be fast involved with the proper iris area segmentation from the pixel value calculation of frame difference among the images which were detected with two adjacent open-eye and close-eye pictures. This proposed iris recognition could be fast processed with the proper grid size of the eye region, and designed with the frame difference between the adjacent images from the USB-OTG interface with this camera module with the restrict of searching area in face and iris location. As a result, the detection time of iris location can be reduced, and this module can be expected with eliminating the standby time of eye-open.

• Korean Journal of Applied Biomechanics
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• v.20 no.2
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• pp.239-243
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• 2010

The putting stroke accounts for 40~50% of total stroke for a golf rounding and most golfers have difficulties on the puting. Studies for the putting stroke have been conducted by analyzing various factors such as kinematics, kinetics, psychologic and physiologic parameters. A lot of devices were developed to support the studies. However there was no appropriate method to measure the position of the ball quantitatively. In this study, we developed a new measurement system to measure and evaluate the putting result. The developed system uses a USB camera to take the 2-dimensional image of the surface including the hole cup at the center of the image and the ball. The position of the ball is extracted as a set of distance and angle in polar coordinate system. We evaluated the new system with an indoor set-up for putting experiments and the system provided accurate measurement results. The proposed system can be combined with the other measurement systems such as 3D motion capture system and force plate without any restriction.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.807-813
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• 2016

Recently, a spherical pendulum attached to an end-effector of a robot manipulator has been frequently used for a test bed of residual vibration suppression control in a multi-dimensional motion. However, there was no automatic tracking system to detect the current bob position on-line, and there was inconvenience to not be able to store the bob position in real time and plot the trajectory. In this study, we developed a two-dimensional, real-time bob-detecting system using a digital USB camera, of which the key is hardware component design and software C programming for fast image processing and interfacing. The developed system was applied to residual vibration suppression control of a two-dimensional spherical pendulum that is attached at the end-effector of a two degree-of-freedom SCARA robot, and the effectiveness of the developed system has been demonstrated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.535-538
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• 2022

For Plug & Play of IoT devices, we develop a module that recognizes the type of USB, which is a typical wired interface of IoT devices, through image recognition. In order to drive an IoT device, a driver for communication and device hardware is required. The wired interface for connecting to the IoT device is recognized by using the image obtained through the camera of smartphone shooting to recognize the corresponding communication interface. For USB, which is a most popular wired interface, types of USB are classified through artificial neural network-based machine learning. In order to secure sufficient data set of artificial neural networks, USB images are collected through the Internet, and additional image data sets are secured through image processing. In addition to the convolution neural networks, recognizers are implemented with various deep artificial neural networks, and their performance is compared and evaluated.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.534-536
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• 2018

본 논문은 Depth 카메라보다 가격이 저렴한 USB 카메라를 이용하여 Marker 인식을 하였으며 또한 Marker의 크기에 따른 거리 측정을 하였다. 이를 통해 Manipulator를 제어하는데 있어 부피가 큰 Depth 카메라를 이용하지 않고 부피가 작은 USB 카메라를 이용하여 제어하는데 용이함을 Simulation으로 확인을 하였다. Depth 카메라처럼 영상 속에 깊이를 통해 거리 측정을 하는 것이 아닌 Marker의 크기에 따른 거리 측정을 하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.5
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• pp.157-163
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• 2016

This paper presents Finger Keyboard which detects the user's key types on a keyboard drawn on the paper using a video camera. The Finger Keyboard software was written in standard C/C++ language and thus easy to port to other computing environments. We installed a popular USB-type web camera on a Windows PC and implemented the Finger Keyboard as a Windows application which detects key typing and then injects the key code into the message queue of the Windows operating system. Also we implemented the Finger Keyboard on the Raspberry Pi 2 embedded computer with a dedicated camera and connected it to the Android device as an external keyboard through the Bluetooth. The result of experiments showed that the average ratio of recognition success is around 80% at the typing speed of 120 characters per minute.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.505-506
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• 2008

Motion capture system that is used in movies and games today requires large equipments and expensive that it is still not common as a reasonable family game. Therefore, this research project focused on solving these problems mentioned above and move on to develop a new type of approach and by using reasonable family use USB camera and augmented reality to develop a bodily sensation motion capture system which can be used in making a video game. In order to develop this, I used a pair of Marker which can be placed on both hands and one USB camera and the image that was extracted in real time goes through the AR toolkit and ed the 3D coordinates of data and developed a motion capture system.