• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.565-578
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• 2018

In this paper, we investigate the feasibility of modelling image strips, instead of individual scenes, that have been acquired from the same orbital pass through the process of bundle adjustments. Under this approach, First, a rational function model (RFM) of the strip image is generated from the RFMs of individual images, such that the entire strip of images can be treated as a single image. Correction parameters are calculated through bundle adjustments between strip images. For the experiment, we used two stereo strips. Each strip image consists of three KOMPSAT-3A scenes. Experimental results show that it was possible to improve the initial model by using the control points located in a specific region of the strip. We showed that absolute orientation with moderate accuracy of 2 m errors were achieved from 12 ground control points for the three-image strips. The test results indicate that bundle adjustment of strip images could be more efficient than bundle adjustments of the individual scenes.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.217-219
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• 2010

Sensor modeling is the basic step to extract and to use the information from satellite images. Sensor modeling requires ground control points. If we use a single image, we have limitations on modeling about images captured from regions that we can not approach or take GCPs. In this research, we use strip images to do sensor modeling by two methods. At first, we apply sensor modeiling to single image and apply the results by extrapolation. Next, we consider strip images to single image. As a result, we find the second method is more accurate about whole image.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.335-340
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• 2013

Purpose: This study was performed to develop a lateral flow strip sensor for the detection of pathogenic Escherichia coli O157:H7 in various samples. Also, feasibility of using an image analysis method to improve the interpretation of the strip sensor was evaluated. Methods: The lateral flow strip sensor has been fabricated based on nitrocellulose lateral-flow membrane. Colloidal gold and E. coli O157:H7 antibodies were used as a tag and a receptor, respectively. Manually spotted E. coli O157:H7 antibody and anti-mouse antibody on nitrocellulose membrane were used as test and control dots, respectively. Feasibility of the lateral flow strip sensor to detect E. coli O157:H7 were evaluated with serially diluted E. coli O157:H7 cells in PBS or food samples. Test results of the lateral flow strip sensor were measured with an image analysis method. Results: The intensity of the test dot started to increase with higher concentration of the cells were introduced. The sensitivities of the sensor were both $10^4$ CFU/mL Escherichia coli O157:H7 spiked in PBS and in chicken meat extract, respectively. Conclusions: The lateral flow strip sensor and image analysis method could detect E. coli O157:H7 in 20 min, which is significantly quicker than conventional plate counting method.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3056-3059
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• 2000

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.11
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• pp.1156-1161
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• 2006

This paper describes a fast image labeling algorithm for the feature extraction of connected components. Labeling the connected regions of a digitized image is a fundamental computation in image analysis and machine vision, with a large number of application that can be found in various literature. This algorithm is designed for the surface defect inspection of Cold Mill Strip. The labeling algorithm permits to separate all of the connected components appearing on the Cold Mill Strip.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1999.08a
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• pp.201-207
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• 1999

The automatic pinhole detection system is described. The goal of this project is to study the feasibility test of the new concept for hole detection. The developed method is able to detect almost 50$\mu\textrm{m}$ pinhole by evaluating the shining of the light as if there is pinhole in the strip. Moreover, it is possible to inspect up to the 200$\mu\textrm{m}$ inclined pinhole. The system cosists of three main functional parts: the source part of the light which is using the linear halogen lamp, the image gathering part which is using a line CCD and the image processing part. The light spot can be controlled and optimized corresponding to the situation of the strip. To eliminate back ground noise, the binary image processing method is adopted.

• KSTLE International Journal
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• v.2 no.1
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• pp.80-84
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• 2001

The purpose of this paper is to show the result from the study to improve the formability and appearance which is important in the cold rolled strip, the coated strip and prepainted strip. Furthermore, to give appropriate surface roughness, shape of work roll for temper mill is also important. The strip has a greater peak counts and homogeneous roughness. This makes the prepainted surface smooth and consistent in appearance with good image clarity. Therefore, the surface roughness of the work roll is very important. The reason that surface roughness of the work roll is transferred to the strip surface is the rolling farce and tension at the temper rolling or cold rolling. This study is classified in order to get an accurate and homogeneous roughness. There are few papers published in this field, because its importance is not known and the proper operation of the machine is not generally well known. This paper investigates the correlation between strip surface roughness and the surface of the work roll. After studying the surface roughness and shape according to the texturing method for roll surfaces at temper rolling, the findings were as follows. Irregular surface roughness can be compensated with several paint coatings, but this also makes the quality deteriorate and manufacturing costs go up.

• Journal of the Korean Institute of Telematics and Electronics
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• v.9 no.2
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• pp.1-16
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• 1972

In this paper, the characteristics of linearly tapered strip-line filters, where the even-mode and odd-mode characteristic impedances vary linearly with the same degree along the lines, are analyzed. The Impedance parameters of linearly tapered coupled strip-line, which is made by connecting two linearly tapered unsymmetric coupled strip-lines In cascade and the I:no input and output terminals are made equal, are obtained. Using the above parameters, the Image parameters of linearly tapered coupled strip-line filters are derived. The result of analysis shows that the line length can be made shorter and also the stop-band width between the fundamental and second pass-band becomes wider, compared with the coupled strip-line filters which use uniform strip-lines. Furthermore, the difference of impedance levels in the fundsmental and second pass-band becomes larger with the degree of taper of the lines. This property is unique, in comparison with the case of uniform or exponentially tapered strip-line filters.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.115-120
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• 2000

This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.123.1-123
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• 2001

For Autonomous navigation of the mobile robots, the robots' capability to recognize 3D environment is necessary. In this paper, an on-line 3D map building method for autonomous mobile robots is proposed. To get range data on the environment, we use an sensor system which is composed of a structured light and a CCD camera based on optimal triangulation. The structured laser is projected as a horizontal strip on the scene. The sensor system can rotate $\pm$ $30{\Circ}$ with a goniometer. Scanning the system, we get the laser strip image for the environments and update planes composing the environment by some image processing steps. From the laser strip on the captured image, we find a center point of each column, and make line segments through blobbing these center poings. Then, the planes of the environments are updated. These steps are done on-line in scanning phase. With the proposed method, we can efficiently get a 3D map about the structured environment.