• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.142-147
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• 2012

Machining tool conditions directly affect to quality of product and productivity of manufacturing. Many researches performed for tool condition monitoring in machining process to improve quality and productivity. Conventional methods use characteristics of signal for cutting force, motor current consumption, vibration of machine tools and machining sound. Recently, diameter of machining tool is become smaller for minimizing of mechanical parts. Tool condition monitoring using conventional methods are relatively difficult because micro machining using small diameter tool has low machining load and high cutting speed. These days, the direct monitoring for tool conditions using vision system is performed actively. But, vision system is affected by external conditions such as back ground of image and illumination. In this study, minimizing technology of external conditions using distribution analysis of image data are developed in micro machining using small diameter drill and tap. The image data is gathered from vision system. Several sets of experiment results are performed to verify the characteristics of the proposed machining technology.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.270-278
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• 2000

A machine vision system using charge coupled device(CCD) camera for the weed detection in a radish farm was developed. Shape features were analyzed with the binary images obtained from color images of radish and weeds. Aspect, Elongation and PTB were selected as significant variables for discriminant models using the STEPDISC option. The selected variables were used in the DISCRIM procedure to compute a discriminant function for classifying images into one of the two classes. Using discriminant analysis, the successful recognition rate was 92% for radish and 98% for weeds. To recognize radish and weeds more effectively than the discriminant analysis, an artificial neural network(ANN) was used. The developed ANN model distinguished the radish from the weeds with 100%. The performance of ANNs was improved to prevent overfitting and to generalize well using a regularization method. The successful recognition rate in the farms was 93.3% for radish and 93.8% for weeds. As a whole, the machine vision system using CCD camera with the artificial neural network was useful to detect weeds in the radish farms.

• Journal of Biosystems Engineering
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• v.32 no.4
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.3
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• pp.213-219
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• 2014

This study applied the data of 384 senior citizens over 65 years old having difficulties in everyday life, among the ageing research panel of Korea Labor Institute in 2000, due to their visual impairment in the final analysis to investigate factors affecting the use of vision aids by the aged with visual impairment. The analysis was based on the service usage Andersen-Newman model and the factors were classified into preceding factors, potential factors and desire factors. To examine the effects of each factors on the use of vision aids by the aged with visual impairment, logistic regression analysis was carried out. In the analysis results, the level of vision aids usage was shown to increase significantly with unemployed status and higher education level in the preceding factors, lower subjective stratum consciousness in the potential factors, and higher cognitive function in the desire factors. The limitation and implication of this study were suggested on the basis of the results.

• Journal of Environmental Health Sciences
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• v.30 no.2
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• pp.108-114
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• 2004

Observation of microorganisms collected from contaminated soils has been mainly conducted by using microscopy. Microscopic measurement is occupied an important part of the microorganism experiment, and is used as an important tool to count microorganisms as well as to observe cellular form and mode of life in the field of soil microbe observation. In general, observation equipments for soil microbes consist of electron microscope, camera, frame grabber (image acquisition baud), and image analysis software. Because image analysis software should be linked with frame grabber most equipments have to be imported as the package form. Therefore, the observation system is very expensive and difficult to be operated. In this study, soil microbes＇ observation equipment with the vision system which is easy operated and cheaper than imported one was developed and tested. The efficiency of image capturing and data aquisition with developed frame grabber and software in this experiment was good enough to analyze the image of soil microorganism.

• Journal of Advanced Navigation Technology
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• v.27 no.5
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• pp.685-689
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• 2023

The proposed system in the study aims to detect forest fires in real-time stream data received from the drone-camera. Recently, the number of wildfires has been increasing, and also the large scaled wildfires are frequent more and more. In order to prevent forest fire damage, many experiments using the drone camera and vision analysis are actively conducted, however there were many challenges, such as network speed, pre-processing, and model performance, to detect forest fires from real-time streaming data of the flying drone. Therefore, this study applied image data processing works to capture five good image frames for vision analysis from whole streaming data and then developed the object detection model based on YOLO_v2. As the result, the classification model performance of forest fire images reached upto 93% of accuracy, and the field test for the model verification detected the forest fire with about 70% accuracy.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.170-173
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• 2001

To apply stereo vision system to obstacle recognition system of AGV, we constructed algorithm of stereo matching and distance measuring with stereo image for positioning of object in area. And using this system, we look into the error between real position and measured position, and studied relationship of compensation.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.80-92
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• 2016

The purpose of this study is to analyze the visions of visual landscape planning and to suggest improvements for it. This study overviews currents methods of making the vision of visual landscape planning by group interview with hands-on workers. Thirty-two cases of visual landscape planning are reviewed to analyze the forms and contents of vision of visual landscape planning. The purpose of urban vision and city slogans are fairly similar to the vision of visual landscape planning; therefore, this study reviews and compares them. According to this study, we conducted writing direction and policy implications. The results of this study are as follows. The vision of visual landscape planning is written by consulting the landscape resources survey and visions of upper plans. These writing methods are able to enhance the consistency of each chapter in visual landscape planning, and the consistency between visual landscape planning and upper plans. Thus, it is desirable to revise landscape planning guidelines with this method. The current vision of visual landscape planning is written in the form of a city slogan. But the vision of visual landscape planning is not a means of publicity and transformational use. So, the form of the vision needs to be revised. This study analyzed the correlation among the vision of visual landscape planning, urban vision, and city slogan. There is a closer correspondence between the vision of visual landscape planning and urban vision than city slogan. This result means that it is beneficial to write the vision of visual landscape planning in consideration of the upper plan. Henceforward, for maintaining and enhancing consistency detailed contents in landscape planning guidelines are needed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.3
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• pp.16-24
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• 2011

The vehicle electronic control system is being developed as the legal and social demand for ensuring driver's safety is rising. The various Driver Assistance Systems with various sensors such as radars, camera, and lasers are in practical use because of the falling price of hardware and the high performance of sensor and processer. In the preceding study of this research, the program was developed to recognize the experiment vehicle's driving lane and the cars nearby or approaching the experiment vehicle throughout the images taken by CCD camera. In addition, the 'dangerous driving analysis program' which is Vision System basis was developed to analyze the cause and consequence of dangerous driving. However, the Vision system developed in the previous studyhad poor recognition rate of lane and vehicles at the time of passing a tunnel, sunrise, or sunset. Therefore, through mounting the brightness response algorithm to the Vision System, the present study is aimed to analyze the causes of driver's dangerous driving clearly by improving the recognition rate of lane and vehicle, regardless of when and where it is.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.30-34
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• 2006

Recently, there has been an increasing demand for computer-vision-based inspection and/or measurement system as a part of factory automation equipment. In general, it is almost impossible to check the fault of all parts, coming from part-feeding system, with only manual inspection because of time limitation. Therefore, most of manual inspection is applied to specific samples, not all coming parts, and manual inspection neither guarantee consistent measuring accuracy nor decrease working time. Thus, in order to improve the measuring speed and accuracy of the inspection, a computer-aided measuring and analysis method is highly needed. In this paper, a computer-vision-based pipe inspection system is proposed, where the front and side-view profiles of three different kinds of pipes, coming from a forming line, are acquired by computer vision. And the edge detection is processed by using Laplace operator. To reduce the vision processing time, modified Hough transform is used with clustering method for straight line detection. And the center points and diameters of inner and outer circle are found to determine eccentricity of the parts. Also, an inspection system has been built so that the data and images of faulted parts are stored as files and transferred to the server.