• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.1
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• pp.1-6
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• 1983

To give the recognition capability of task objects by computer vision to a sensor-based robot system, an image digitizer and some basic software techniques were developed and repofted here. The image digitizer was developed with the CROMEMCO SYSTEM III microcomputer anti C.C.T.V. camera to convert the analog valued scene into digitized image which could be pro-cessed by a digital computer. Basic software techniques for the computer vision system were aimed at the recognition of 3-dimensional objects. Experiments with these techniques were carried out using the image of a cubicle which could be considered as typical simple 3-dimensional object.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.133-139
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• 2013

This paper proposes a vision-based indoor localization method for autonomous vehicles. A single upward-facing digital camera was mounted on an autonomous vehicle and used as a vision sensor to identify artificial landmarks and any natural corner features. An interest point detector was used to find the natural features. Using an optical flow detection algorithm, information related to the direction and vehicle translation was defined. This information was used to track the vehicle movements. Random noise related to uneven light disrupted the calculation of the vehicle translation. Thus, to estimate the vehicle translation, a Kalman filter was used to calculate the vehicle position. These algorithms were tested on a vehicle in a real environment. The image processing method could recognize the landmarks precisely, while the Kalman filter algorithm could estimate the vehicle's position accurately. The experimental results confirmed that the proposed approaches can be implemented in practical situations.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.495-500
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• 2002

Recently, a service robot industry outstands as an up and coming industry of the next generation. Specially, there are so many research in self-steering movement(SSM). In order to implement SSM, robot must effectively recognize all around, detect objects and make a surrounding map with sensors. So, many robots have a sonar and a infrared sensor, etc. But, in these sensors, We only know informations about between the robot and the object as well as resolution faculty is of inferior quality. In this paper, we will introduce new algorithm that recognizes objects around robot and makes a two dimension surrounding map with a omni-direction vision camera and two stereo vision cameras.

• Journal of Biosystems Engineering
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• v.19 no.4
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• pp.369-379
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• 1994

A computer vision system consisted of a microscope, a CCD camera, a frame grabber and a personal computer was used to analyze spraying pattern. An algorithm was developed for the system to measure size of droplets including overlapped droplets, to count number of droplets, and to estimate spray deposition in a certain area from the data obtained. A series of experiment was carried out to test validity of the algorithm. The experiment resulted that accuracy of the droplet size measurement, accuracy of counting the number of droplets and the estimation of spray deposition were within an acceptable range. It was concluded from the results that the computer vision system operated by the developed algorithm is very useful tool to analyze spraying pattern.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.555-555
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• 2000

This study is concentrated on the development of hight speed multi-object image processing algorithm, and based on these a1gorithm, vision control scheme is developed for the robot's position control in real time. Recently, the use of vision system is rapidly increasing in robot's position centre. To apply vision system in robot's position control, it is necessary to transform the physical coordinate of object into the image information acquired by CCD camera, which is called image processing. Thus, to control the robot's point position in real time, we have to know the center point of object in image plane. Particularly, in case of rigid body, the center points of multi-object must be calculated in a image plane at the same time. To solve these problems, the algorithm of multi-object for rigid body control is developed.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.408-408
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• 2000

A parabolic dish concentrator used in a high temperature application of solar energy tracks the sun's movement by two axis sun tracking system. In such a system, sun tracking performance affects the system efficiency directly. Generally the higher the tracking accuracy is, the better the system performance is. A large number of parabolic dish type concentrators has been developed and implemented in the world. However none of them clearly provided a qualitative method of how the accuracy of the sun tracking system can be evaluated. The work presented here is the evaluation of sun tracking performance of parabolic dish concentrator, which follows the sun's movement by the sensor, using computer vision system. We install a camera on the parabolic dish concentrator. While the concentrator follows the sun, sun's images are captured continuously. Then the performance of sun tracking system was evaluated by analyzing the variation of the position of the sun in the images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.733-737
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• 1996

This paper presents a method to measure tile position and orientation of a prismatic polyhedral object (of unknown width, length, height, and number of vertices) using machine vision. The width, length, and origin of workplace where an object is lying are defined as Preliminary operation. The edges of an object are detected from captured image using least sum of square error. The information of an object is determined from the geometric relationships between edges. As an user interface, a versatile image processing program is developed in several modules, and renders a very useful 3D measurement at a limited constraints when adopted in automation of production process. The flexibility of camera position from the algorithm developrf can be used for automated pick and place operations and feeding workpiece u: ;ing assembly robot.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.36-48
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• 2010

This paper is concerned with stereo vision-based approach to detect obstacles and to generate the path of destination from the start. The hexapod robot in the experiment is cable of walking by legs and driving by wheels simultaneously. The hexapod robot operates under the driving mode normally, and it changes driving mode to walking mode to overcome obstacles using its legs. Disparity map, which is the correlation between two images taken by stereo camera, is employed for calculation of the distance between the robot and obstacles. When the obstacles information is extracted from the disparity map, the potential field algorithm is applied to create the obstacle-avoidance path. Simulator, based on OpenGL, is developed to generate the graphical path, and the experimental results are shown for the verification of the proposed algorithm.

• Journal of Environmental Health Sciences
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• v.30 no.2
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• pp.108-114
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• 2004

Observation of microorganisms collected from contaminated soils has been mainly conducted by using microscopy. Microscopic measurement is occupied an important part of the microorganism experiment, and is used as an important tool to count microorganisms as well as to observe cellular form and mode of life in the field of soil microbe observation. In general, observation equipments for soil microbes consist of electron microscope, camera, frame grabber (image acquisition baud), and image analysis software. Because image analysis software should be linked with frame grabber most equipments have to be imported as the package form. Therefore, the observation system is very expensive and difficult to be operated. In this study, soil microbes＇ observation equipment with the vision system which is easy operated and cheaper than imported one was developed and tested. The efficiency of image capturing and data aquisition with developed frame grabber and software in this experiment was good enough to analyze the image of soil microorganism.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.266-270
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• 2016

In this paper, we propose a technique of drowsiness detection using machine vision. The drowsiness of vehicle driver is often the primary cause of motor vehicle accidents. Therefore, the checking of eye images for detecting drowsiness status of driver is critical for preventing these accidents. In our suggested method, we analyze the changes of histogram and edge of eye region images which are acquired using CCD camera. We developed a drowsiness detection system using the histogram and edge change information. The experimental results show that our proposed method enhances the accuracy of detecting drowsiness nearly to 98%, and can be used for preventing vehicle accidents due to the drowsiness of drivers.