• Agricultural and Biosystems Engineering
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• v.6 no.2
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• pp.47-53
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• 2005

AMachine vision is a promising tool for the autonomous guidance of farm machinery. Conventional CCD camera for the machine vision needs a desktop PC to install a frame grabber, however, a web camera is ready to use when plugged in the USB port. A web camera with a notebook PC can replace existing camera system. Autonomous steering control system of this research was intended to be used for combine harvester. If the web camera can recognize cut/uncut edge of crop, which will be the reference for steering control, then the position of the machine can be determined in terms of lateral offset and heading angle. In this research, a white line was used as a cut/uncut edge of crop for steering control. Image processing algorithm including capturing image in the web camera was developed to determine the desired travel path. An experimental vehicle was constructed to evaluate the system performance. Since the vehicle adopted differential drive steering mechanism, it is steered by the difference of rotation speed between left and right wheels. According to the position of vehicle, the steering algorithm was developed as well. Evaluation tests showed that the experimental vehicle could travel within an RMS error of 0.8cm along the desired path at the ground speed of $9\sim41cm/s$. Even when the vehicle started with initial offsets or tilted heading angle, it could move quickly to track the desired path after traveling $1.52\sim3.5m$. For turning section, i.e., the curved path with curvature of 3 m, the vehicle completed its turning securely.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.5
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• pp.529-535
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• 2009

This paper describes a measuring device of glass thickness using machine vision and image processing techniques on real-time. Today, the machine vision enable to inspect fast and exactly than human's eyes. The presented system has advantages of continuous measurement, flexibility and good accuracy. The system consists of a laser diode, a CCD camera with PC. The camera located on the opposite side of the incident beam measures the distance between two reflected laser beams from the glass top and bottom surface. We apply a binary algorithm to convert and analyze the image from camera to PC. Laser point coordination by border tracing algorithm is used to find the center of beam circle. The measured result was compared with micrometer and showed 0.002mm accuracy. Finally, the errors were discussed how to minimize the influence of glass wedge angle and angular error of moving stage.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.2
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• pp.121-125
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• 2021

The machine vision technology has been widely used in the industrialized nations like the United States, Japan, and EU in the various industries from the late 1980s. Machine vision inspection system mainly consists of a camera, optics, illumination and an image acquisition system. Optimization of the illumination light source is very important. This paper shows a comparison between Pulse Width Modulation (PWM) control and strobe control in driving LED lighting system for machine vision. PWM control method has problems such as a temperature rising of LED and a flickering in image measurement for inspection. In contrast, the proposed strobe control method can suppress the temperature of LED light source below 40℃. Also, it can remove the flickering problem through a synchronization between a frame grabber and a camera shutter. Finally, the strobe control method was shown to extract clearer images with a high precision compared to PWM control method.

• Proceedings of the KIEE Conference
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• 2003.11b
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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 of Precision Engineering Conference
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• 1995.10a
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• pp.255-258
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• 1995

Surface profile is an important paramerer to evaluate accuracy of machined worpiece. It is necessary to acquire this data by in-process measurement. Recent researchers have introduced Machine Vision technique to achieve it. But it is difficult to apply it to industry field yet. In this study, in-process measuring system of surface profile is developed using CCD camera. The effect of illuminance according to incident angle is investigated and surface profile from surface tester and illuminance graph are compared experimentally.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.4
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• pp.41-52
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• 2014

In this paper, O-ring size measurement algorithm based on a small machine vision inspection equipment which can replace a expensive and large machine vision inspection equipment is presented. The small machine vision inspection equipment acquires a image from a CCD camera shooting a measurement plane which located on a back light and the proposed size measurement algorithm is apply to the image. For improvement of size measurement accuracy, camera lens distortion correction and perspective distortion correction are conducted by software technique. Consider O-ring's shape, ellipse fitting model is applied. In order to increase the reliability of ellipse fitting, RANSAC algorithm is applied.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.3
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• pp.24-30
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• 2007

The FPCs(Flexible Printed Circuit) are currently used in several electronic products like digital cameras, cellular phones because of flexible material characteristics. Because the FPC is usually small size and flexible, only one FPC should not enter chip mounting process, instead, several FPCs are placed on the large rigid pallette and enter into the chip mounting process. Currently the job of mounting FPC on the pallette is carried by totally manual way. Thus, the goals of the research is develop the automatic machine of FPC mounting on pallette using vision alignment. Instead of using two cameras or using moving one camera, the proposed vision system with only one fixed camera is adopted. Moreover, the two picker heads which can handle two FPCs simultaneously are used to make process time shortened. The procedure of operation is firstly to measure alignment error of FPC, correct alignment errors, and finally mount well-aligned FPC on the pallette. The vision technology is used to measure alignment error accurately, and precision motion control is used in correcting errors and mounting FPC.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.105-114
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• 2003

In this study, a dicing machine with vision system was built and an algorithm for automatic alignment was developed for dual camera system. The system had a macro and a micro inspection tool. The algorithm was formulated from geometric relations. When a wafer was put on the cutting stage within certain range, it was inspected by vision system and compared with a standard pattern. The difference between the patterns was analyzed and evaluated. Then, the stage was moved by x, y, $\theta$ axes to compensate these differences. The amount of compensation was calculated from the result of the vision inspection through the automatic alignment algorithm. The stage was moved to the compensated position and was inspected by vision for checking its result again. Accuracy and validity of the algorithm was discussed from these data.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.2
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• pp.94-103
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• 2004

The vision system model used for this study involves the six parameters that permits a kind of adaptability in that relationship between the camera space location of manipulable visual cues and the vector of robot joint coordinates is estimated in real time. Also this vision control method requires the number of cameras to transform 2-D camera plane from 3-D physical space, and be used irrespective of location of cameras, if visual cues are displayed in the same camera plane. Thus, this study is to investigate the optimal number of cameras used for the developed vision control system according to the change of the number of cameras. This study is processed in the two ways : a) effectiveness of vision system model b) optimal number of cameras. These results show the evidence of the adaptability of the developed vision control method using the optimal number of cameras.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.867-875
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• 2004

In order to inspect burr geometry and hole quality in micro-drilling processes, a cost-effective method using an image processing and shape from focus (SFF) methods on the machine tool is proposed. A CCD camera with a zoom lens and a novel illumination unit is used in this paper. Since the on-machine vision unit is incorporated with the CNC function of the machine tool, direct measurement and condition monitoring of micro-drilling processes are conducted between drilling processes on the machine tool. Stainless steel and hardened tool steel are used as specimens, as well as twist drills made of carbide are used in experiments. Validity of the developed system is confirmed through experiments.