• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.802-811
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• 1996

Farmers need alternatives for weed control due to the desire to reduce chemicals used in farming. However, conventional mechanical cultivation cannot selectively remove weeds located in the seedline between crop plants and there are no selective heribicides for some crop/weed situations. Since hand labor is costly , an automated weed control system could be feasible. A robotic weed control system can also reduce or eliminate the need for chemicals. Currently no such system exists for removing weeds located in the seedline between crop plants. The goal of this project is to build a real-time , machine vision weed control system that can detect crop and weed locations. remove weeds and thin crop plants. In order to accomplish this objective , a real-time robotic system was developed to identify and locate outdoor plants using machine vision technology, pattern recognition techniques, knowledge-based decision theory, and robotics. The prototype weed control system is composed f a real-time computer vision system, a uniform illumination device, and a precision chemical application system. The prototype system is mounted on the UC Davis Robotic Cultivator , which finds the center of the seedline of crop plants. Field tests showed that the robotic spraying system correctly targeted simulated weeds (metal coins of 2.54 cm diameter) with an average error of 0.78 cm and the standard deviation of 0.62cm.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.184-191
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• 2004

In this study, an inspection system for automotive parts using machine vision has been developed and presented. The system is comprised of six analog CCD cameras, frame grabber, and mechanism that loads the automotive parts to the system for the inspection. An Image processing algorithm for detecting eight different types of defects of oil-seals are developed, and the effectiveness of the algorithm is experimentally verified. Inspection process is completed in 1 second with acceptable accuracy. It is envisaged that this inspection system will have a wide application in the automotive part manufacturing industry in the future.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1041-1051
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• 2014

In this paper, we propose a new image alignment technique based on CUDA SURF in order to solve the initial image alignment problem that frequently occurs in machine vision applications. Machine vision systems using multi-spectral images have recently become more common for solving various decision problems that cannot be performed by the human vision system. These machine vision systems mostly use markers for the initial image alignment. However, there are some applications where the markers cannot be used and the alignment techniques have to be changed whenever their markers are changed. In order to solve these problems, we propose a new image alignment method for multi-spectral machine vision applications based on SURF extracting image features without depending on markers. In this paper, we propose an image alignment method that obtains a sufficient number of feature points from multi-spectral images using SURF and removes outlier iteratively based on a least squares method. We further propose an effective preliminary scheme for removing mismatched feature point pairs that may affect the overall performance of the alignment. In addition, we reduce the execution time by implementing the proposed method using CUDA based on GPGPU in order to guarantee real-time operation. Simulation results show that the proposed method is able to align images effectively in applications where markers cannot be used.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.2
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• pp.92-99
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• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding systems, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, novel presented, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.85-96
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• 2000

An Eggcrate assembly is an important part to hold and support 16,000 tubes containing hot and contaminated water in the steam generator of nuclear power plant. As a great number of tubes should be inserted into the eggcrate assembly, the dimensions of each eggcrate grid are one of the critical factors to determine the availability of tube insertion. in this paper. we propose a machine vision algorithm for measuring the inner-circle diameter of each eggcrate grid whose shape is not exact quadrangular. The overall procedure of the algorithm is composed of camera calibration, eggcrate image preprocessing, grid height adjustment, and inner-circle diameter estimation. The algorithm is tested on real specimens and the results show that the algorithm works fairly well.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.795-801
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• 1998

In this paper, we propose a machine vision algorithm for inspecting inserts which are used for milling and turning operations. Major defects of the inserts are breakage and crack on insert surfaces. Among the defects, breakages on the face of the inserts can be detected through three stages of the algorithm developed in this paper. In the first stage, a multi-layer perceptron is used to recognize the inserts being inspected. Edge detection of the insert image is performed in the second stage. Finally, in the third stage breakages on the insert face are identified using Hough transform. The overall algorithm is tested on real specimens and the results show that the algorithm works fairly well.

• 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.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.983-986
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• 2007

Concrete surface grinding is required for flatness and adhesiveness of concrete surface. The procedure is, however, labor intensive and has a hazardous work condition. Also, the productivity and the quality of concrete surface grinding depend on the levels 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. 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 graphic MMI 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.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1511-1515
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• 2004

Machine vision system plays an important role in factory automation. Its many applications are found in automobile manufacturing industries, as an eye for robotic automation system. In this paper, an automobile position measuring vision system(APMVS) applicable to manufacturing line for under body painting of a car is introduced. The APMVS measures position and orientation of the car body to be sealed or painted by the robots. The configuration of the overall robotic sealing/painting system, design and application procedure, and application examples are described.