• The Transactions of The Korean Institute of Electrical Engineers
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• 제58권10호
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• pp.2041-2046
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• 2009

In this paper, we propose the feature points extraction method of hand region using vision. To do this, first, we find the HCbCr color model by using HSI and YCbCr color model. Second, we extract the hand region by using the HCbCr color model and the fuzzy color filter. Third, we extract the exact hand region by applying labeling algorithm to extracted hand region. Fourth, after finding the center of gravity of extracted hand region, we obtain the first feature points by using Canny edge, chain code, and DP method. And then, we obtain the feature points of hand region by applying the convex hull method to the extracted first feature points. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.

• Journal of the Semiconductor & Display Technology
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• 제9권3호
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• pp.65-69
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• 2010

The stereoscopic vision system is the algorithm to obtain the depth of target object of stereo vision image. This paper presents an efficient disparity matching method using nagao filter, octree color quantization and dynamic programming algorithm. we describe methods for performing color quantization on full color RGB images, using an octree data structure. This method has the advantage of saving a lot of data. We propose a preprocessing stereo matching method based on Nagao-filter algorithm using color information. using the nagao filter, we could obtain effective depth map and using the octree color quantization, we could reduce the time of computation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제16권1호
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• pp.221-225
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• 2016

This paper is about vision system that exhibits automatic examination of the conditions of fuses and relay boxes using a camera. Proposed vision system is composed of three parts: image acquisition, vision algorithm, and user interface. The image acquisition part is composed of illumination and optics. The vision algorithmis the examining part, using the grabbed fuse box image. Lastly, user interface is divided into two parts, user interface for registering features of fuse box and user interface for examination operation.

• Proceedings of the KIEE Conference
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 A
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• pp.231-234
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• 2003

This paper describes the structure, operation, image processing, and decision making techniques of a color machine vision system designed for the automatic sorting of soybeans. The system consists of feeder, conveyor belt, line-scan camera, lights. ejector, and a PC Unlike manufactured goods, agricultural products including soybeans have quite uneven features. The criteria for sorting good and bad beans also vary depending on inspectors. We tackle these problem by letting the system learn the inspecting parameters from good samples selected manually by a machine user before running the system for sorting. Real-time processing has another importance In the design. Four parallel DSPs are employed to increase the processing speed. When the designed system was tested with real soybeans and the result was successful.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 한국농업기계학회 1998년도 동계 학술대회 논문집
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• pp.374-379
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• 1998

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제10권2호
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• pp.67-80
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• 2006

In this paper, we propose a new pointing device that is replaced a mouse as the pointing device with. For reducing the existing pointing device's problem which had marker and high-cost, we develop a new pointing device using computer vision like as a similar human vision system. The proposed system first carries out a real-time movement tracking system using image data which are segmented by color modeling, and finally does the pointing action by 3-D coordinate calculated from stereo geometry information resulting from stereo matching of the segmented region.

• Journal of Biosystems Engineering
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• 제25권1호
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• pp.55-62
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• 2000

Autonomous farm operation needs to be developed for safety, labor shortage problem, health etc. In this research, an autonomous tractor for tillage was investigated using machine vision and a fuzzy logic controller(FLC). Tractor heading and offset were determined by image processing and a geomagnetic sensor. The FLC took the tractor heading and offset as inputs and generated the steering angle for tractor guidance as output. A color CCD camera was used fro the image processing . The heading and offset were obtained using Hough transform of the G-value color images. 15 fuzzy rules were used for inferencing the tractor steering angle. The tractor was tested in the file and it was proved that the tillage operation could be done autonomously within 20 cm deviation with the machine vision and the FLC.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제5권6호
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• pp.1157-1162
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.587-591
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• 2001

This paper deals with inspect algorithm using visual system. One of the major problems that arise during polymer production is the estimation of the noise of the color product.(bad pallets) An erroneous output can cause a lot of losses (production and financial losses). Therefore new methods for real-time inspection of the noise are demanded. For this reason, we have presented a development of vision system algorithm for the defect inspection of PE color pallets. First of all, in order to detect the edge of object, the differential filter is used. And we apply to the labelling algorithm for feature extraction. This algorithm is designed for the defect inspection of pallets. The labelling algorithm permits to separate all of the connected components appearing on the pallets. Labelling the connected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. Also, we suggested vision processing program in window environment. Simulations and experimental results demonstrate the performance of the proposal algorithm.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2009년도 정보 및 제어 심포지움 논문집
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• pp.222-224
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• 2009

This paper presents an algorithm that extracts road lane's specific information by using HSI color information and performance enhancement of lane detection base on vision processing of drive assist. As a preprocessing for high speed lane detection, the optimal extraction of region of interest for lane boundary(ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled and it also increases reliabilities by deleting edges those are misrecognized. Road lane is extracted with simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since noise can be removed by using saturation and brightness of HSI color model. Also it searches for the road lane's color information and extracts characteristics. The real road experimental results are presented to evaluate the effectiveness of the proposed method.