• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.140-152
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• 2017

This Paper is for A study of sensor fusion using Radar sensor and Vision sensor in moving object detection. Radar sensor has some problems to detect object. When the sensor moves by wind or that kind of thing, it can happen to detect wrong object like building or tress. And vision sensor is very useful for all area. And it is also used so much. but there are some weakness that is influenced easily by the light of the area, shaking of the sensor device, and weather and so on. So in this paper I want to suggest to fuse these sensor to detect object. Each sensor can fill the other's weakness, so this kind of sensor fusion makes object detection much powerful.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.14-20
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• 2009

The goal of image processing is to improve the visual appearance of images for human viewers. The histogram is an important tool which can be used as basic data of digital image processing. Therefore, to effectively manage a histogram in digital image processing is very important. Currently machine vision systems are used in many appearance inspection fields instead of inspection by human. However, the appearance inspection result by machine vision system is mainly influenced by illumination of workplace. In this paper, we propose a histogram transform method for improving accuracy of machine visual inspection. The enhancement effect of area feature is obtained by performing proposed histogram transformation in area that needs improvement The proposed algorithm is verified by appearance inspection of jig plate samples.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.61-66
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• 2010

A stereo vision, which is based on two or more images taken from different view points, is able to build three dimensional maps of its environment having various applications including robots and home networks. SAD algorithm, which is based on area-based correlation, is widely used since its regular structure provide abundant parallelism. In this paper, we present heuristic designs of SAD algorithm to meet the demands on accuracy and resource usages in various applications. The disparity abridgement and the window abridgement algorithms can be used for vision systems in low cost and small size. The window shape algorithm can be applicable when object are in specific shapes. The adaptive window algorithm work well when accuracy is the primary concern.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.9 s.174
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• pp.99-106
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• 2005

In recent years, vision sensors are widely used to mobile robot for navigation or exploration. The analog signal transmission of visual data being used in this area, however, has some disadvantages including noise weakness in view of the data storage. A large amount of data also makes it difficult to use this method for a mobile robot. In this paper, a digital data compressing technology based on MPEG4 which substitutes for analog technology is proposed to overcome the disadvantages by using DWT(Discreate Wavelet Transform) instead of DCT(Discreate Cosine Transform). The TI Company's DSP chip, TMS320C6711, is used for the image encoder, and the performance of the proposed method is evaluated by PSNR(Peake Signal to Noise Rates), QP(Quantization Parameter) and bitrate.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.293-293
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• 2010

In this paper, we propose a stereo vision based monitoring concept for passenger's safety on railroad platform. In general, basic concept of stereo image processing technique uses the correlations between left and right images, and extracts additional distance information. It provides easy removal of ambient illumination changes, which has been difficult to achieve with conventional 2D based image processing technique. In the paper, we present developed stereo camera and stereo vision based detection algorithm in order to monitor possible accidents at platform area, and verified the detection performance of proposed system with experimental results.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.354-362
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• 2000

In Korea, researches on year-round leaf vegetables production system are in progress, most of them focused on environmental control. Therefore, automation technologies for harvesting, transporting, and grading are in great demand. A robot system for harvesting lettuces, composed of a 3-DOF (degree of freedom) manipulator, an end-effector, a lettuce feeding conveyor, an air blower, a machine vision system, six photoelectric sensors, and a fuzzy logic controller, was developed. A fuzzy logic control was applied to determine appropriate grip force on lettuce. Leaf area index and height were used as input variables and voltage as an output variable for the fuzzy logic controller. Success rate of the lettuce harvesting was 94.12%, and average harvesting time was approximately 5 seconds per lettuce.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.658-667
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• 1996

A computer vision system was developed to automatically detect and locate the oyster hinge line, one step in shucking an oyster. The computer vision system consisted of a personal computer, a color frame grabber, a color CCD video camera with a zoom lens, two video monitor, a specially designed fixture to hold the oyster, a lighting system to illuminate the oyster and the system software. The software consisted of a combination of commercially available programs and custom designed programs developed using the Microsoft CTM . Test results showed that the image resolution was the most important variable influencing hinge detection efficiency. Whether or not the trimmed -off-flat-white surface area was dry or wet, the oyster size relative to the image size selected , and the image processing methods used all influenced the hinge locating efficiency. The best computer software and hardware combination used successfully located 97% of the oyster hinge lines tested. This efficienc was achieve using camera field of view of 1.9 by 1.5cm , a 180 by 170 pixel image window, and a dry trimmed -off oyster hinge end surface.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.554-557
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• 2002

This paper describes power potential field method for the collision-free path planning of stereo-vision based mobile robot. Area based stereo matching is performed for obstacle detection in uncertain environment. The repulsive potential is constructed by distributing source points discretely and evenly on the boundaries of obstacles and superposing the power potential which is defined so that the source potential will have more influence on the robot than the sink potential when the robot is near to source point. The mobile robot approaches the goal point by moving the robot directly in negative gradient direction of the main potential. We have investigated the possibility of power potential method for the collision-free path planning of mobile robot through various experiments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.4 no.1
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• pp.25-31
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• 2008

In this paper, we propose a new method that separates background and foreground from stereo images. This method can be improved automatic target tracking system by using disparity map of the stereo vision system and background-separating mask, which can be obtained camera configuration parameters. We use disparity map and camera configuration parameters to separate object from background. Disparity map is made with block matching algorithm from stereo images. A morphology filter is used to compensate disparity error that can be caused by occlusion area. We could obtain a separated object from background when the proposed method was applied to real stereo cameras system.