• Agricultural and Biosystems Engineering
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• v.1 no.1
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• pp.22-29
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• 2000

The development of bio-response feedback control system known as the speaking plant approach has been a challenging task for plant production engineers and scientists. In order to achieve the aim of developing such a bio-response feedback control system, the primary concern should be to develop a practical non-invasive technique for monitoring plant growth. Those who are skilled in raising plants can sense whether their plants are under adequate water conditions or not, for example, by merely observing minor color and tone changes before the plants wilt. Consequently, using machine vision, it may be possible to recognize changes in indices that describe plant conditions based on the appearance of growing plants. The interpretation of image information of plants may be based on image features extracted from the original pictorial image. In this study, the performance of a finite element retina was optimized by a genetic algorithm. The optimized finite element retina was evaluated based on the performance of neural plant growth monitor that requires input data given by the finite element retina.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.125-131
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• 1999

In this paper, the algorithms which can track the two dimensional moving circular object using simple vision system are described. In order to track the moving object, the process of finding the object feature points - such as centroid of the object, corner points, area - is indispensable. With the assumption of two-dimensional circular moving object, the centroid of the circular object is computed from three points on the object circumference. Different kinds of algorithms for computing three edge points - simple x directional detection method, stick method. T-shape method are suggested. Through the computer simulation and experiments, three algorithms are compared from the viewpoint of detection accuracy and computational time efficiency.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.674-676
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• 1999

본 연구에서는 시각센서를 이용하여 CAD데이터와 측정치와의 오차를 실시간으로 판정하여 다양한 형태의 불량검사 및 부품분류를 할 수 있는 2D 측정용 Machine Vision System을 개발하였다. 또한, 본 시스템은 품질검사 및 수율 관리를 하여 제품의 품질을 향상시킬 수 있도록 하기 위한 품질관리 제어시스템이다. 이를 위하여, 고성능 카메라와 서브픽셀, 레이블링, 켈리브레이션등의 최첨단 영상처리 기술을 개발하여 고속 온-라인 상에서 가공물의 치수를 정확하게 측정(10 ${\mu}m$ 단위)할 수 있도록 하였다.

• Journal of Mechanical Science and Technology
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• v.14 no.10
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• pp.1104-1113
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• 2000

This paper proposes an efficient reverse engineering technique for compound surfaces using a boundary detection method. This approach consists in extracting geometric edge information using a vision system, which can be used in order to drastically reduce geometric errors in the vicinity of compound surface boundaries. Through the image-processing technique and the interpolation process, boundaries are reconstructed by either analytic curves (e. g. circle, ellipse, line) or parametric curves (B-spline curve). In other regions, except boundaries, geometric data are acquired on CMM as points inspected using a touch type probe, and then they are interpolated on several surfaces using a B-spline skinning method. Finally, the boundary edge and the skinned surfaces are combined to reconstruct the final compound surface. Through simulations and experimental works, the effectiveness of the proposed method is confirmed.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2769-2771
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• 2000

In this paper we propose new algorithms of path planning and obstacle avoidance for an autonomous mobile robot with vision system. Distance variation is included in path planning to approach the target point and avoid obstacles well. The fuzzy rules are also applied to both trajectory planning and obstacle avoidance to improve the autonomy of mobile robot. It is shown by computer simulation that the proposed algorithm is working well.

• Journal of Sensor Science and Technology
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• v.22 no.6
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• pp.393-399
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• 2013

We propose a method of sensing the rotation and distance of a camera by using a fisheye lens system as a vision sensor. We estimate the rotation angle of a camera with a modified correlation method by clipping similar regions to avoid symmetry problems and suppressing highlight areas. In order to eliminate the rectification process of the distorted points of a fisheye lens image, we introduce an offline process using the normalized focal length, which does not require the image sensor size. We also formulate an equation for calculating the distance of a camera movement by matching the feature points of the test image with those of the reference image.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1218-1230
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• 2019

This study proposes a novel video traffic flow detection method based on machine vision technology. The three-frame difference method, which is one kind of a motion evaluation method, is used to establish initial background image, and then a statistical scoring strategy is chosen to update background image in real time. Finally, the background difference method is used for detecting the moving objects. Meanwhile, a simple but effective shadow elimination method is introduced to improve the accuracy of the detection for moving objects. Furthermore, the study also proposes a vehicle matching and tracking strategy by combining characteristics, such as vehicle's location information, color information and fractal dimension information. Experimental results show that this detection method could quickly and effectively detect various traffic flow parameters, laying a solid foundation for enhancing the degree of automation for traffic management.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.348-357
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• 2018

The topic of anomaly detection is one of the emerging research themes in computer vision, computer interaction, video analysis and monitoring. Observers focus attention on behaviors that vary in the magnitude or direction of the motion and behave differently in rules of motion with other objects. In this paper, we use this information and propose a system that detects abnormal behavior by using simple features extracted by optical flow. Our system can be applied in real life. Experimental results show high performance in detecting abnormal behavior in various videos.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.45-45
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• 2000

This paper proposes a remote control system that combines computer network and an autonomous mobile robot. We control remotely an autonomous mobile robot with vision via the internet to guide it under unknown environments in the real time. The main feature of this system is that local operators need a World Wide Web browser and a computer connected to the internet communication network and so they can command the robot in a remote location through our Home Page. The hardware architecture of this system consists of an autonomous mobile robot, workstation, and local computers. The software architecture of this system includes the server part for communication between user and robot and the client part for the user interface and a robot control system. The server and client parts are developed using Java language which is suitable to internet application and supports multi-platform. Furthermore, this system offers an image compression method using motion JPEG concept which reduces large time delay that occurs in network during image transmission.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.278-287
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• 2013

Modern information technologies continue to provide industries with new and improved methods. With the rapid development of Machine to Machine (M2M) communication, a smart container supply chain management is formed based on high performance sensors, computer vision, Global Positioning System (GPS) satellites, and Globle System for Mobile (GSM) communication. Existing supply chain management has limitation to real time container tracking. This paper focuses on the studies and implementation of real time container chain management with the development of the container identification system and automatic alert system for interrupts and for normal periodical alerts. The concept and methods of smart container modeling are introduced together with the structure explained prior to the implementation of smart container tracking alert system. Firstly, the paper introduces the container code identification and recognition algorithm implemented in visual studio 2010 with Opencv (computer vision library) and Tesseract (OCR engine) for real time operation. Secondly it discusses the current automatic alert system provided for real time container tracking and the limitations of those systems. Finally the paper summarizes the challenges and the possibilities for the future work for real time container tracking solutions with the ubiquitous mobile and satellite network together with the high performance sensors and computer vision. All of those components combine to provide an excellent delivery of supply chain management with outstanding operation and security.