• 한국생산제조학회지
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• 제7권4호
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• pp.64-72
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• 1998

This paper a new approach to the design of machine vision technique with a camera modeling that accounts for major sources of geometric distortion, namely, radial, decentering, and thin prism distortion. Radial distortion causes an inward or outward displacement of a given image point from its ideal location. Actual optical systems are subject to various degrees of decentering , that is , the optical centers of lens design and manufacturing as well as camera assembly. It is our propose to develop the vision system for the pattern recognition and the automatic test of parts and to apply the line of manufacturing. The performance of proposed vision system is illustrated by simulation and experiment.

• 대한기계학회논문집A
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• 제30권6호
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• pp.713-721
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• 2006

Micro-drill wear deteriorates accuracy and productivity of the micro components. In order to improve productivity and qualify of micro components, it is required to investigate micro-drill wear exactly. In this study, a machine vision system is proposed to measure the wear of micro-drills using a precision servo stage. Calibration experiments are conducted to compensate for the machine vision system. In this paper, worn volume, area and length are defined as wear amounts. Micro-drill wear is reconstructed as the 3D topography and the quantized wear amount by using the shape from focus (SFF) method and wear parameters. Experiments have been conducted with HSS twist micro-drills and SM45C carbon steel workpieces. Validity of the proposed machine vision system is confirmed through experiments.

• 한국멀티미디어학회논문지
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• 제21권1호
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• pp.51-60
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• 2018

We present a real-time interactive particle-art with human motion based on computer vision techniques. We used computer vision techniques to reduce the number of equipments that required for media art appreciations. We analyze pros and cons of various computer vision methods that can adapted to interactive digital media art. In our system, background subtraction is applied to search an audience. The audience image is changed into particles with grid cells. Optical flow is used to detect the motion of the audience and create particle effects. Also we define a virtual button for interaction. This paper introduces a series of computer vision modules to build the interactive digital media art contents which can be easily configurated with a camera sensor.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.881-884
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• 2000

Foveated vision has the big advantage of exhibiting a wide field of view, along with a high resolution fovea. However, in the case of using optical flow, foveated vision kas one demerit. The demerit is a concentrate of optical flow. For foveated vision, an object moves almost only around the center of the field. In this paper, we suggest how to segment motion of some objects, and how to discriminate a hand and another object. In the future, the method we suggested may be useful for recognizing human actions by foveated vision.

• 한국생산제조학회지
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• 제26권1호
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• pp.50-58
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• 2017

This paper proposes a real-time robotic vision control scheme using the weighting matrix to efficiently process the vision data obtained during robotic movement to a target. This scheme is based on the vision system model that can actively control the camera parameter and robotic position change over previous studies. The vision control algorithm involves parameter estimation, joint angle estimation, and weighting matrix models. To demonstrate the effectiveness of the proposed control scheme, this study is divided into two parts: not applying the weighting matrix and applying the weighting matrix to the vision data obtained while the camera is moving towards the target. Finally, the position accuracy of the two cases is compared by performing the slender bar placement task experimentally.

• 디지털산업정보학회논문지
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• 제11권3호
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• pp.1-9
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• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.

• Smart Structures and Systems
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• 제17권6호
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• pp.935-956
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• 2016

With the help of advanced image acquisition and processing technology, the vision-based measurement methods have been broadly applied to implement the structural monitoring and condition identification of civil engineering structures. Many noncontact approaches enabled by different digital image processing algorithms are developed to overcome the problems in conventional structural dynamic displacement measurement. This paper presents three kinds of image processing algorithms for structural dynamic displacement measurement, i.e., the grayscale pattern matching (GPM) algorithm, the color pattern matching (CPM) algorithm, and the mean shift tracking (MST) algorithm. A vision-based system programmed with the three image processing algorithms is developed for multi-point structural dynamic displacement measurement. The dynamic displacement time histories of multiple vision points are simultaneously measured by the vision-based system and the magnetostrictive displacement sensor (MDS) during the laboratory shaking table tests of a three-story steel frame model. The comparative analysis results indicate that the developed vision-based system exhibits excellent performance in structural dynamic displacement measurement by use of the three different image processing algorithms. The field application experiments are also carried out on an arch bridge for the measurement of displacement influence lines during the loading tests to validate the effectiveness of the vision-based system.

• 대한한방내과학회지
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• 제39권2호
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• pp.217-223
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• 2018

In this study, five cases of post-stroke vision disorders are presented. The patients had no distinctive change in vision disorders before Korean medical treatment, which included herbal medicine, acupuncture, and electroacupuncture. After 11 to 28 days of Korean medical treatment, the patients experienced the first improvement of vision disorders after stroke. Also, patients who received Korean medical treatment after 30 days from onset, the duration in which the most improvement of post-stroke vision disorders occurs, progressed their vision disorders by the start of Korean medical treatment. Korean medical treatment might be effective in treating vision disorders after stroke.

• 한국정보전자통신기술학회논문지
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• 제12권6호
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• pp.605-611
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• 2019

3D Vision system has many applications recently but popularization have many problems that need to be overcome. Volumetric display may process a amount of visual data and design the high efficient vision system for display. In case of stereo system for volumetric display, disparity vectors from the stereoscopic sequences and residual images with the reference images has been transmitted, and the reconstructed stereoscopic sequences have been displayed at the receiver. So central issue for the design of efficient volumetric vision system lies in selecting an appropriate stereo matching and robust vision system. In this paper, we propose high efficient vision system with the reduction of rectification error which can perform the 3D data extraction efficiently with low computational complexity. In experimental results with proposed vision system, the proposed method can perform the 3D data extraction efficiently with reducing rectification error and low computational complexity.

• Journal of Biosystems Engineering
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• 제32권3호
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• pp.160-165
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• 2007

This study was conducted to evaluate beef using a color machine vision system. The machine vision system has an advantage to measure larger area than a colorimeter and also could measure other quality factors like distribution of fats. However, the machine vision measurement is affected by system components. To measure the beef color with the machine vision system, the effect of color balancing control was tested and calibration model was developed. Neural network for color calibration which learned reference color patches showed a high correlation with colorimeter in L*a*b* coordinates and had an adaptability at various measurement environments. The trained network showed a very high correlation with the colorimeter when measuring beef color.