• Journal of Biosystems Engineering
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• v.32 no.3
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• pp.179-189
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• 2007

Most of the seeds of cucurbitaceous rootstock species used for grafting were mainly sown by hand. This study was carried out to develop an on-line discriminating algorithm of seed direction using machine vision and an automatic seeding system. The seeding system was composed of a supplying device, feeding device, machine vision system, reversing device, seeding device and system control section. Machine vision was composed of a color CCD camera, frame grabber, image inspection chamber, lighting and personal computer. The seed image was segmented into a region of seed part and background part using thresholding technique in which H value of HSI color coordinate system. A seed direction was discriminated by comparing position between the center of circumscribed rectangle to a seed and the center of seed image. It took about 49ms to identify and redirect seed. Line-up status of seed was good the more than 95% of a sowed seed. Seeding capacity of this system was shown to be 10,140 grains per hour, which is three times faster than that of a typical worker.

• Journal of Practical Engineering Education
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• v.6 no.1
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• pp.37-42
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• 2014

The automated visual inspection system (machine vision system) for quality assurance is important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. There is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we present the implementation of line scan camera based equipment for technical training of the automated visual inspection system. The training system consists of the X-Y stage which is widely used in machine vision industries and its variable image resolution are set to $10-30{\mu}m$. Additionally, this training system can attach the industrial illumination, either the direct illuminator or coaxial illuminator, for verifying the effect of illuminations. This means that the trainee can have a practical training in various equipment conditions and the training system is similar to the automated visual inspection system in industries.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1683-1691
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• 2013

Concrete surface grinding is frequently used for flatness of concrete surface, concrete pavement rehabilitation, and adhesiveness in pavement construction. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding highly depend on the skills of worker. Thus, the development of remote controlled concrete surface grinding equipment is necessary to prevent the environmental pollution and to protect the workers from hazardous work condition. However, it is difficult to evaluate the grinded surface objectively in a remote controlled system. Also, The machine vision system developed in this study takes the images of grinded surface with the network camera for image processing. Then, by representing the quality test results to the integrated program of the remote control station, the quality control system is constructed. The machine vision algorithm means the image processing algorithm of grinded concrete surface and this paper presents the objective quality control standard of grinded concrete surface through the application of the suggested algorithm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.95-99
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• 2006

A tape feeder of a SMD(Surface Mount Device) mounter is a device that sequentially feeds electronic components on a tape reel to the pick-up system of the mounter. As components are getting much smaller, feeding accuracy of a feeder becomes one of the most important factors for successful component pick-up. Therefore, it is critical to keep the feeding accuracy to a specified level in the assembly and production of tape feeders. This paper describes a tape feeder inspection system that was developed to automatically measure and to inspect feeding accuracy using machine vision. It consists of a feeder base, an image acquisition system, and a personal computer. The image acquisition system is composed of CCD cameras with lens, LED illumination systems, and a frame grabber inside the PC. This system loads up to six feeders at a time and inspects them automatically and sequentially. The inspection software was implemented using Visual C++ on Windows with easily usable GUI. Using this system, we can automatically measure and inspect the quality of ail feeders in production process by analyzing the measurement results statistically.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4145-4150
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• 2010

This research aims to design on an automatic machine vision system to replace eye inspection of alternator spool which is one of the key automotive parts. The alternator spool, plastic extrusion part would have various defects like unfinished, crack and burr. Through the design failure examples the optimized fast machine vision system will be designed to inspect all spools also focuses on the low cost machine for the middle sized company as 2'nd automotive supplier. 3-dimensional design softwares of Pro-Engineer & CATIA were used and the system were built based on the design. The system will contribute to satisfy the cycle time and can inspect each part in an absolutely accurate method, which is sufficient for industrial applications.

• The Journal of Korean Institute for Practical Engineering Education
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• v.4 no.2
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• pp.91-97
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• 2012

The automated visual inspection system (machine vision system) for quality assurance is an important factory automation equipment in the manufacturing industries, such as display, semiconductor, etc. The world market of the machine vision components is expected 18 billon dollars in 2015. Therefore, there is a lot of demand for the machine vision engineers. However, there are no technical training courses for machine vision technologies in vocational schools, colleges and universities. In this paper, we propose a technical training program for the machine vision technology. The total time of training is 30 to 60 hours and the training program can operate flexibly by student's major, a priori knowledge and education level.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.54-55
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• 2008

• Journal of Mechanical Science and Technology
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• v.18 no.7
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• pp.1055-1061
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• 2004

In this research, a vision system for detecting breakages of small-diameter taps, which are rarely detected by the indirect in-process monitoring methods such as acoustic emission, cutting torque and motor current, was developed. Two HMI (Human Machine Interface) programs to embed the developed vision system into a Siemens open architecture controller, 840D, were developed. They are placed in sub-windows of the main window of the 840D and can be activated or deactivated either by a softkey on the operating panel or the M code in the NC part program. In the event that any type of tool breakage is detected, the HMI program issues a command for an automatic tool change or sends an alarm signal to the NC kernel. An evaluation test in a high-speed tapping machine showed that the developed vision system was successful in detecting breakages of small-diameter taps up to M1.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.951-954
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• 1998

This paper describes the implementation of the machine vision system and the method of classifying the objects. Its system described in this paper is consisted of robot, conveyer system, warehouse, and machine vision. This system first recognizes the object on conveyer, and then robot moves it to the warehouse. The position of the object on conveyer is always not constant, because it is not easy to extract the feature of its object and classify it into one of several categories. In this paper, to classify or inspect the pattern of the object, we propose the method of template matching using feature vector such as position invariant moment and mophological operation such as opening and closing. And we indentified an unregistered object using unsuperviser learning method and assigned it to the new pattern. We implemented its system and obtained satisfied results.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.3
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• pp.397-406
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• 1998

The purpose of this research is to develop an integrated quality inspection system using machine vision technology in the automotive engine assembly process. The system makes it possible for the inspected data to be entered directly from the machine vision system into the developed system without the need for intermediate operations. Such direct entry enables prompt corrective actions against process problems. An IVP-150 machine vision board is installed an the PC for image processing, and a template matching technology is implemented to precisely verify quality factors. The developed system is successfully installed in a manufacturing process, and it showed robustness to the problems of noise, distortion, and orientation.