• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.309-310
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• 2006

This paper is about the development of surface inspection of bearing inner and outer race using machine vision. Before this system is developed, most inspections are performed by workers' naked eye. To improve both the inconvenience and incorrectness, another new tester is introduced. This system has the three sections mainly. First one is the mechanism section which transfers bearing manufactured from previous process line to the testing process in plant. Another is the inspection system which is composed of two parts: computer vision and measurement system using laser diode which inspects the defects of the bearing inner or outer race. The other is the pneumatic cylinder part controlled by Programmable Logic Controller(PLC). The system which is developed shows favorable results, and that has the advantage of convenience and correctness compared to previous system.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.301-306
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• 2012

We propose a method for accurate image acquisition in a machine vision system in the present study. The most important feature is required by the various lenses to implement real and of the same high quality image-forming optical role. The input of the machine vision system, however, is generated due to the aberration of the lens distortion. Transformation defines the relationship between the real-world coordinate system and the image coordinate system to solve these problems, a mapping function that matrix operations by calculating the distance between two coordinates to specify the exact location. Tolerance Focus Lens caused by the lens aberration correction processing to Galvanometer laser precision machining operations can be improved. Aberration of the aspheric lens has a two-dimensional shape of the curve, but the existing lens correction to linear time-consuming calibration methods by examining a large number of points the problem. How to apply the Bilinear interpolation is proposed in order to reduce the machining error that occurs due to the aberration of the lens processing equipment.

• Journal of Biosystems Engineering
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• v.35 no.6
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• pp.443-449
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• 2010

A machine vision-based instrument to measure a droplet size spectrum of a spray nozzle was developed and tested to evaluate its accuracy on measuring spray droplet sizes and classifying nozzle sizes. The instrument consisted of a machine vision, light emitting diode (LED) illumination and a desktop computer. The illumination and machine vision were controlled by the computer through a C++ program. The program controlled the machine vision to capture droplet images under controlled illumination, and processed the droplet images to characterize the droplet size distribution of a spray nozzle. An image processing algorithm was developed to improve the accuracy of the system by eliminating random noise and out-of-focus droplets in droplet images while measuring droplet sizes. The instrument measured sizes of the three different balls (254.0, 497.8 and $793.8\;{\mu}m$) and the measurement ranges were $241.2-273.6\;{\mu}m$, $492.9-529.6\;{\mu}m$ and $800.8-824.1\;{\mu}m$ for 254.0-, 497.84- and $793.75-\;{\mu}m$ balls, respectively. Error of the measured droplet mean was less than 3.0 %. Droplet statistics, $D_{V0.1}$, $D_{V0.5}$ and $D_{V0.9}$, of a reference nozzle set were measured, and droplet size spectra of five spray nozzles covering from very fine to extremely coarse were measured to classify spray nozzle sizes. Ninety percent of the classification results of the instrument agreed with manufacturer's classification. A comparison study was carried out between developed and commercial instruments, and measurement results of the developed instrument were within 20 % of commercial instrument results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.1339-1343
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• 2004

This paper presents a development of the control algorithm and Pick & Placer. The Pick & Placer provides a powerful multi-task system that includes both graphical and remote interface. Users can easily set up sorting parameters and record important data including wafer number, data, and operator information. This System sets up a dustproof device and massively machined components to provide an extremely stable sorting environment. Precise resolution and accuracy result from using machine vision, a pneumatic slide drive and close -looped positioning.

• Journal of Korean Society for Quality Management
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• v.32 no.1
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• pp.63-74
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• 2004

Recently, enterprises have focused on quality improvement for delighting their customers. Especially, all business sector have checked, analyzed their consumer complaints in detail on their products and made a plan to reduce them. But there is a limitation not to solve them. This paper presents one of tools to reduce non qualified product on their operation line directly by modernized IT technology after analyzing and making the plan.

• Journal of Biosystems Engineering
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• v.42 no.3
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• pp.227-233
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• 2017

Purpose: Morphological properties of soybean roots are important indicators of the vigor of the seed, which determines the survival rate of the seedlings grown. The current vigor test for soybean seeds is manual measurement with the human eye. This study describes an application of a machine vision technique for rapid measurement of soybean seed vigor to replace the time-consuming and labor-intensive conventional method. Methods: A CCD camera was used to obtain color images of seeds during germination. Image processing techniques were used to obtain root segmentation. The various morphological parameters, such as primary root length, total root length, total surface area, average diameter, and branching points of roots were calculated from a root skeleton image using a customized pixel-based image processing algorithm. Results: The measurement accuracy of the machine vision system ranged from 92.6% to 98.8%, with accuracies of 96.2% for primary root length and 96.4% for total root length, compared to manual measurement. The correlation coefficient for each measurement was 0.999 with a standard error of prediction of 1.16 mm for primary root length and 0.97 mm for total root length. Conclusions: The developed machine vision system showed good performance for the morphological measurement of soybean roots. This image analysis algorithm, combined with a simple color camera, can be used as an alternative to the conventional seed vigor test method.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1997.06c
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• pp.238-246
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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, a manipulator, a gripper and plug tray transfer system. The performance of the robotic transplanter was tested and compared by two different transplanting methods, which were to consider the leaf orientation of seedlings and not to. Results of this study were as follows. (1) A cartesian coordinate manipulator for a robotic transplanter with 3 degree of freedom was constructed. The accuracy of position control was $\pm$1 mm. (2) The robotic transplanter with the machine vision system, the manipulator, the gripper and the transfer system was developed and tested with a shovel-type finger. Without considering the orientation of leaves, the success rates of transplanting healthy cucumber seedlings in 72-cell and 128-cell plug-trays were 95.5% and 94.5% respectively. Considering the orientation of leaves, the success rates of transplanting healthy cucumber seedling in 72-cell and 128-cell plug-trays were 96.0% and 95.0% respectively.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.4
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• pp.30-36
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• 2004

The development of LD(Laser Diode) tester and its control system based on the graphical programming language(LabVIEW) is addressed. The ill tester is used to check the optic power and the optic spectrum of the LD Chip. The emitter size of LD chip and the diameter of the Detector(optic fiber and photo diode) are very small, therefore the test device needs high accuracy. But each motion part of the test device could not accomplish high accuracy due to the limit of the mechanical performance. So, an image processing with machine vision is proposed to compensate for the error. By adopting our method we can reduce the error of position within $\pm$5$\mu\textrm{m}$.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.35-43
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• 2002

The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

• The Transactions of the Korea Information Processing Society
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• v.7 no.6
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• pp.1973-1979
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• 2000

Driving the need for machine vision system is growing consumer demand for quality and defect-free products. Especially it is the most important in tarpaulin's manufacturing process achieves automatically by machine vision instead of by man vision. In this paper pinholes detection is performed by using morphology algorithms. Top hat transform is one of morphology applications. This transform take high performance of defect detection in the case that unexpected changes occur in some non-uniform background. For pinholes defect, automatic visual inspection system has been developed, which was composed by a line-scan camera, illumination, a frame grabber, a motor driver and control units. This system has excellent capacity to defect pinholes to the 0.1 mm by 0.5 mm in size and to work in moving objects by maximum 20 m/min in speed.