• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.403-404
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• 2008

This report described the development of Vision Inspector program which can simulate numerically the image acquisition process of Machine Vision System for automatic optical inspection of any products. The program consists of an illuminator, a product to be inspected, and a camera with image sensor, and the final image obtained by ray tracing.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.796-799
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• 1996

광섬유는 코어(Core), 클레드(Clad), 그리고 1,2차 코팅(Coating)으로 구성되어 있다. 본 연구에서는 광섬유의 코팅에 생기는 결함의 유무 및 종류와 크기를 분류하는 Vision System을 구현하였다. 전처리 과정으로, CCD Camera를 이용하여 얻은 화상에 대하여 Sobel 연산자로 경계선을 추출하고, 문턱값(Threshold Value)을 적용하여 이진 화상을 만든다. 외경 정보 추출을 위하여, 투영 정보, 수리 형태학(Mathematical Morphology)적 연산을 수행하고, 결함의 종류와 크기를 효율적으로 분류하도록 Tree Classifier를 설계하였다. 실험 결과로서 각 결함 별 오차율, 전체 오차율(Total Error Rate)등을 제시하였다.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.29-38
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• 2001

A navigation system was developed for autonomous guidance of a combine. It consisted of a DGPS, a machine vision system, a gyro sensor and an ultrasonic sensor. For an autonomous operation of the combine, target points were determined at first. Secondly, heading angle and offset were calculated by comparing current positions obtained from the DGPS with the target points. Thirdly, the fuzzy controller decided steering angle by the fuzzy inference that took 3 inputs of heading angle, offset and distance to the bank around the rice field. Finally, the hydraulic system was actuated for the combine steering. In the case of the misbehavior of the DGPS, the machine vision system found the desired travel path. In this way, the combine traveled straight paths to the traget point and then turned to the next target point. The gyro sensor was used to check the turning angle. The autonomous combine traveled within 31.11cm deviation(RMS) on the straight paths and harvested up to 96% of the whole rice field. The field experiments proved a possibility of autonomous harvesting. Improvement of the DGPS accuracy should be studied further by compensation variations of combines attitude due to unevenness of the rice field.

• Journal of Bio-Environment Control
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• v.6 no.1
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• pp.55-65
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• 1997

This study was conducted to develop a robotic transplanter for bedding plants. The robotic transplanter consisted of machine vision system, manipulator attached with the specially designed gripper, and plug tray transfer system. Results of this study were as follows. 1. A machine vision system for a robotic transplanter was developed. The success rates of detecting empty cells and bad seedlings in 72-cell and 128-cell plug-trays for cucumber seedlings were 98.8％ and 94.9％ respectively. The success rates of identifying leaf orientation for 72- cell and 128-cell plug-trays were 93.5% and 91.0%, respectively. 2. A cartesian coordinate manipulator for a robotic transplanter with 3 degrees of freedom was constructed. The accuracy of position control was $\pm$ 1mm. 3. The robotic transplanter was tested with a shovel-type finger. Without considering leaf orientation, the success rates of transplanting healthy cucumber seedlings for 72-cell and 128-cell plug-trays were 95.5% and 94.5%, respectively. Considering leaf orientation, the success rates of transplanting healthy cucumber seedling in 72-cell and 128-cell plug-trays were 96.0% and 95.0%, respectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.56-58
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• 2006

Camera calibration in machine vision is the process of determining the intrinsic cameara parameters and the three-dimensional (3D) position and orientation of the camera frame relative to a certain world coordinate system. On the other hand, Takagi-Sugeno-Kang (TSK) fuzzy system is a very popular fuzzy system and approximates any nonlinear function to arbitrary accuracy with only a small number of fuzzy rules. It demonstrates not only nonlinear behavior but also transparent structure. In this paper, we present a novel and simple technique for camera calibration for machine vision using TSK fuzzy model. The proposed method divides the world into some regions according to camera view and uses the clustered 3D geometric knowledge. TSK fuzzy system is employed to estimate the camera parameters by combining partial information into complete 3D information. The experiments are performed to verify the proposed camera calibration.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.127-134
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• 2005

The machine vision has been applied to a number of industrial applications for quality control and automations to improve the manufacturing processes. In this paper, the automation system using the machine vision is developed, which is applicable to the marking process in a steel production process line. The working environment is very harsh to workers so that the automatic system in the steel industry is required increasingly. The developed automatic marking system consists of several mechanical and electrical elements such as the laser position detecting sensor system fur a structured laser beam which is projected to the billet in order to detect the geometry of the billet. An image processing algorithm has been developed to percept the two center positions of a camera and a billet, respectively, and to align two centers. A series of experiments has been conducted to investigate the performance of the proposed algorithm. The results show that two centers of the camera and the billet could be detected very well and differences between two center positions could be also decreased via the proposed location error decreasing algorithm.

• Journal of IKEEE
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• v.28 no.3
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• pp.469-473
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• 2024

In this paper proposes a study on the development of a multi-camera inline inspection system using machine vision for quality inspection of pharmaceutical containers. The proposed technique captures the pharmaceutical containers from multiple angles using several cameras, allowing for more accurate quality assessment. Based on the captured data, the system inspects the dimensions and defects of the containers and, upon detecting defects, notifies the user and automatically removes the defective containers, thereby enhancing inspection efficiency. The development of the multi-camera inline inspection system using machine vision is divided into four stages. First, the design and production of a control unit that fixes or rotates the containers via suction. Second, the design and production of the main system body that moves, captures, and ejects defective products. Third, the design and development of control logic for the embedded board that controls the entire system. Finally, the design and development of a user interface (GUI) that detects defects in the pharmaceutical containers using image processing of the captured images. The system's performance was evaluated through experiments conducted by a certified testing agency. The results showed that the dimensional measurement error range of the pharmaceutical containers was between -0.30 to 0.28 mm (outer diameter) and -0.11 to 0.57 mm (overall length), which is superior to the global standard of 1 mm. The system's operational stability was measured at 100%, demonstrating its reliability. Therefore, the efficacy of the proposed multi-camera inline inspection system using machine vision for the quality inspection of pharmaceutical containers has been validated.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.821-822
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.770-775
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• 1987

In this paper, design and development experiences of a vision based robotic assembly system for electronic components are described. Specifically, the overall system consists of the following three subsystems each of which employs a 16 bit Preprocessor MC 68000 : supervisory controller, real-time vision system, and servo system. The three microprocessors are interconnected using the time shared common memory bus structure with hardwired bus arbitration scheme and operated as a master-slave type in which each slave is functionally fixed in view of software. With this system architecture, the followings are developed and implemented in this research; (i) the system programming language, called 'CLRC', for man-machine interface including the robot motion and vision primitives, (ii) real-time vision system using hardwired chain coder, (iii) the high-precision servo techniques for high speed de motors and high speed stepping motors. The proposed control system were implemented and tested in real-time successfully.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.445-446
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• 2007

The goal of this paper is accuracy improvement of appearance inspection by using image separation average value matching method. The appearance inspection of various electronic products and parts has been executed by the eyesight of human. But inspection by eyesight can't bring about uniform inspection result. Because the appearance inspection result by eyesight of human is changed by condition of physical and spirit of the checker. So machine vision inspection system is currently used to many appearance inspection fields instead of the checker. However the inspection result of machine vision is changed by the illumination of workplace. Therefore we have used a average value matching in this paper for improvement of vision inspection accuracy and could increase inspection accuracy of vision system. In other words, we made an effort for elevation of vision inspection accuracy by making the identical image separation average value of reference image and input image. Also this system has been developed only using PC, CCD Camera and Visual C++ for universal workplace.