• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.428-428
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• 2007

최근 고화질 카메라폰이 경박단소화 되는 경향에 따라 Plastic렌즈 또는 구면 Glass렌즈만으로는 요구되는 광학적 성능 구현이 힘들기 때문에 비구면 Glass렌즈에 대한 요구가 증가하고 있다. 이러한 비구면 Glass렌즈는 일반적으로 초경합금 성형용 코어를 이용한 고온압축 성형방식으로 제작되어지기 때문에 코어면의 초정밀 연삭가공 및 코어면 코팅기술 개발이 시급한 상황이다. 한편, 대표적인 난삭재 Silicon Carbide(SiC)는 광학적 특성 및 기계적 특성, 전기적 특성 등 우수한 특성을 가진 재료로서 우주망원경, 레이저 광 및 X선 반사용 미러 등 다종, 다양한 용도로 이용되고 있으며 전기, 전자, 정보, 정밀기기의 급격한 발전으로 SiC의 수요가 급격히 증가하고 있다. 비구면 Glass렌즈 성형용 코어를 SiC소재로 제작할 경우 성형용 코어의 수명향상, 렌즈 생산원가의 절감 및 코팅 과정의 간소화 등의 다양한 장점을 가지므로 SiC를 이용한 성형용 코어의 나노 정밀도급 초정밀 연삭가공기술의 개발이 필요하다. 본 논문에서는 3 메가픽셀, 2.5배 광학 줌 카메라폰 모듈용 비구면 Glass렌즈 개발을 목적으로 실험계획법을 적용하여 초경합금 성형용 코어의 연삭조건을 규명하였다. 초경합금 비구면 성형용 코어의 초정밀 연삭가공조건 및 결과를 바탕으로 난삭재인 Silicon Cabide(SiC)의 연삭가공조건을 구하고 이를 이용하여 비구면 Glass렌즈 성형용 코어를 초정밀 연삭가공하였다.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.183-188
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• 2010

A factorization-based 3D reconstruction system is realized to recover 3D scene from an image sequence. The image sequence is captured from uncalibrated perspective camera from several views. Many matched feature points over all images are obtained by feature tracking method. Then, these data are supplied to the 3D reconstruction module to obtain the projective reconstruction. Projective reconstruction is converted to Euclidean reconstruction by enforcing several metric constraints. After many triangular meshes are obtained, realistic reconstruction of 3D models are finished by texture mapping. The developed system is implemented in C++, and Qt library is used to implement the system user interface. OpenGL graphics library is used to realize the texture mapping routine and the model visualization program. Experimental results using synthetic and real image data are included to demonstrate the effectiveness of the developed system.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.509-515
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• 2010

In this paper, the mechanism that can walk efficiently in wet land or sand area is proposed. A vision camera is attached to the mechanism, which makes a kind of biologically inspired robot for coast guard. This visionary information enables the biologically inspired robot to react in peripheral environment by a soft-computing algorithm. In addition, the biologically inspired robot can achieve the mission appointed by a programmer connecting with outside, based on RF and Blue-tooth communication module. Therefore, the purpose of this research is the implementation of the biologically inspired robot that can operate most adaptively in sand and wet surface based on Theo Jansen mechanism.

• The Journal of the Korea Contents Association
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• v.19 no.7
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• pp.91-98
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• 2019

The purpose of this study was to develop and test an eye tracker focusing on early childhood participants, based on the characteristics of early childhood eye tracking studies. Eye tracking collects eye movement data of the subject, which provides scientific evidence of human cognition and thinking. The researcher built a Do It Yourself eye tracker camera module from general electronic components, and used Viewpoint analysis software from Arrington Research. The researcher compared the eye tracking data between the DIY eye tracker group and Tobii Pro eye tracker group, which provides a professional eye tracking system. Eye tracking data was collected from 52 five-year old children. The average proportion of valid trials between the two groups was compared with t test, and no significant difference was found. This result indicates that the DIY eye tracker can be used to collect valid eye tracking data from young children under certain research environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.942-943
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• 2016

Stereo gamma ray detection system generates a two-dimensional image of the gamma ray by using the position values and the gamma ray signal. And the device will overlap with the visible light image shows the actual distribution of the gamma-ray space. The gamma ray detection device is a stereo configuration to a motion controller for controlling the signal measurement unit and the position detection portion for detecting the detection portion and the gamma-ray signal comprising a gamma-ray detection sensor. In this paper, we developed a system operation management algorithm for each module individually configured efficiently. We confirmed the imaged and distribution information output for the gamma rays from gamma-ray irradiation test site by using these results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1280-1287
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• 2020

This paper proposes a vision-based food recognition method for automated production of custom cakes. A small camera module mounted on a food art printer recognizes objects' shape and estimates their center points through image processing. Through the perspective transformation, the top-view image is obtained from the original image taken at an oblique position. The line and circular hough transformations are applied to recognize square and circular shapes respectively. In addition, the center of gravity of each figure are accurately detected in units of pixels. The test results show that the shape recognition rate is more than 98.75% under 180 ~ 250 lux of light and the positioning error rate is less than 0.87% under 50 ~ 120 lux. These values sufficiently meet the needs of the corresponding market. In addition, the processing delay is also less than 0.5 seconds per frame, so the proposed algorithm is suitable for commercial purpose.

• Safety and Health at Work
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• v.12 no.4
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• pp.496-504
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• 2021

Background: With the increasing demand for industrial robots and the "noncontact" trend, it is an appropriate point in time to examine whether risk assessments conducted for robot operations are performed effectively to identify and eliminate the risks of injury or harm to operators. This study discusses why robot accidents resulting in harm to operators occur repetitively despite implementing control measures and proposes corrective actions for risk assessments. Methods: This study collected 369 operator-injured robot accidents in Korea over the last decade and reconstructed them into the mechanism of injury, work being undertaken, and bodily location of the injury. Then, through the techniques of Systematic Cause Analysis Technique (SCAT) and Root Cause Analysis (RCA), this study analyzed the root and direct causes of robot accidents that had occurred. Causes identified included physical hazards and complex combinations of hazards, such as psychological, organizational, and systematic errors. The requirements of risk assessments regarding robot operations were examined, and three case studies of robot-involved tasks were investigated. The three assessments presented were: camera module processing, electrical discharge machining, and a panel-flipping robot installation. Results: After conducting RCA and comparing the three assessments, it was found that two-thirds of injury-occurring from robot accidents, causative factors included psychological and personal traits of robot operators. However, there were no evaluations of the identifications of personal aspects in the three assessment cases. Conclusion: Therefore, it was concluded that personal factors of operators, which had been overlooked in risk assessments so far, need to be included in future risk assessments on robot operations.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.2
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• pp.91-96
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• 2022

At the current camera-based technology level, sensor-based basic life pattern recognition technology has to suffer inconvenience to obtain accurate data, and commercial band products are difficult to collect accurate data, and cannot take into account the motive, cause, and psychological effect of behavior. the current situation. In this paper, radar technology for life pattern recognition is a technology that measures the distance, speed, and angle with an object by transmitting a waveform designed to detect nearby people or objects in daily life and processing the reflected received signal. It was designed to supplement issues such as privacy protection in the existing image-based service by applying it. For the implementation of the proposed system, based on TI IWR1642 chip, RF chipset control for 60GHz band millimeter wave FMCW transmission/reception, module development for distance/speed/angle detection, and technology including signal processing software were implemented. It is expected that analysis of individual life patterns will be possible by calculating self-management and behavior sequences by extracting personalized life patterns through quantitative analysis of life patterns as meta-analysis of living information in security and safe guards application.

• Convergence Security Journal
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• v.22 no.1
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• pp.29-38
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• 2022

The importance of prevention of epidemics is increasing due to the serious spread of infectious diseases. For prevention of epidemics, we need to focus on the non-contact industry. Therefore, in this paper, a face recognition door lock that controls access through non-contact is designed and developed. First very simple features are combined to find objects and face recognition is performed using Haar-based cascade algorithm. Then the texture of the image is binarized to find features using LBPH. An non-contact door lock system which composed of Raspberry PI 3B+ board, an ultrasonic sensor, a camera module, a motor, etc. are suggested. To verify actual performance and ascertain the impact of light sources, various experiment were conducted. As experimental results, the maximum value of the recognition rate was about 85.7%.