• Journal of the Korean GEO-environmental Society
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• v.14 no.10
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• pp.49-57
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• 2013

Recently, recycling of the industrial by-products has been an important issue of the Yeosu bay, where large industrial complex is located. Major industrial by-products which are produced from Yeosu industrial complex area are phosphogypsum and flyash, which are about 82% and 10% of the 1.6 million tons industrial by-products. Moreover since the Yeosu industrial complex is located at seaside, phosphogypsum has been pointed as cause of serious environmental contaminant from the regional society. Therefore recycling study can't be delayed anymore. In this paper, artificial aggregate was manufactured by non-sintering process from industrial byproducts - e.g., phosphogypsum and slag - as a geotechnical drainage material. To show the feasibility of the artificial aggregate as a geotechnical drainage material, geotechnical experiments including particle size analysis, permeability test, and large scale direct shear test were carried out. Test results show that the permeability of the artificial aggregates range from $6.94{\times}10^{-1}cm/sec$ to $8.86{\times}10^{-1}cm/sec$, which is much larger value than those are required for the drainage material from the construction specification in Korea, and the friction angle of the artificial aggregate is as large as that of sand in water immersion conditions. From the test results, it was concluded that artificial aggregate made from industrial by-products can be used successfully as a geotechnical drainage material.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.