• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.3
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• pp.175-185
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• 2020

Three-dimensional registration is a process of matching data with or without a coordinate system to a reference coordinate system, which is used in various fields such as the absolute orientation of photogrammetry and data combining for producing precise road maps. Three-dimensional registration is divided into a method using points and a method using linear features. In the case of using points, it is difficult to find the same conjugate point when having different spatial resolutions. On the other hand, the use of linear feature has the advantage that the three-dimensional registration is possible by using not only the case where the spatial resolution is different but also the conjugate linear feature that is not the same starting point and ending point in point cloud type data. In this study, we proposed a method to determine the scale and the three-dimensional translation after determining the three-dimensional rotation angle between two data using quaternion to perform three-dimensional registration using linear features. For the verification of the proposed method, three-dimensional registration was performed using the linear features constructed an indoor and the linear features acquired through the terrestrial mobile mapping system in an outdoor environment. The experimental results showed that the mean square root error was 0.001054m and 0.000936m, respectively, when the scale was fixed and if not fixed, using indoor data. The results of the three-dimensional transformation in the 500m section using outdoor data showed that the mean square root error was 0.09412m when the six linear features were used, and the accuracy for producing precision maps was satisfied. In addition, in the experiment where the number of linear features was changed, it was found that nine linear features were sufficient for high-precision 3D transformation through almost no change in the root mean square error even when nine linear features or more linear features were used.

• Korean journal of applied entomology
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• v.38 no.1
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• pp.53-57
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• 1999

Simple diagnostic kits for monitoring insecticide susceptibility of beet armyworm, Spodoptera exigua (Hiibner) were developed and applied to the field populations. The operation of the kits was based on the correlations between enzyme activities of esterase (EST) and acetylcholinesterase (AChE) and the insecticide susceptibilities. Four different kinds of diagnostic kits (ED, EM, AD, and AM) were designed and classified by diagnostic enzymes (E for esterases and A for acetylcholinesterase) and inhibitors (D for dichlorvos and M for monocrotophos). Diagnostic inhibitor concentrations were 1 mM for ED, 10 mM for EM, 100 mM for AD, and 100 mM for AM. Resistant larvae which were not inhibited by the diagnostic amounts of insecticides developed positive staining (red color), but susceptible~ s howed negative (no color). An insect was used for both EST and AChE diagnostic kits, but different in their samples: hemolymph for EST and the head for AChE. These four diagnostic kits were applied to 1 1 different populations which showed variations of insecticide susceptibilities. Four kits were different in the capability discriminating the insecticide susceptibilites according to insecticides: ED to bifenthrin, AD to methomyl, and ED and AM to chlorpyrifos-methyl. These diagnostic devices can be used for insecticide-resistance management program for this insect pest. It also provide a technical guide to insect pest management for farmers, directors, and researchers.

• Journal of the Korean GEO-environmental Society
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• v.7 no.3
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• pp.5-19
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• 2006

The secondary consolidation settlement of soft clay is generally very little compared to the total settlement and occurs very slowly during long-term period. However the secondary consolidation settlement is comparatively large amount in organic and heavily compressed clay and is a very important engineering factor. In order to reduce residual settlements in reclaimed soft ground, the preloading method is often used. In this study, in order to determine reasonable long-term settlements of large reclaimed site, laboratory incremental loading consolidation tests and surcharging consolidation tests are performed. Sampling was done at Incheon area of west coast and Gwangyang area of south coast in Korea. The characteristics of secondary consolidation have obtained through laboratory tests and analyzed systematically to predict long-term settlements. Additionally, the location data and laboratory test results are correlated by using GIS(geographic information system). The secondary consolidation settlement of the site was predicted based on D/B and the operation technique and estimation technique of space of GIS.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.169-176
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• 2013

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.89-95
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• 2015

In this paper, we propose a real-time two-dimensional bar code detection system even at long range using a vision technique. We first perform short-range detection, and then long-range detection if the short-range detection is not successful. First, edge map generation, image binarization, and connect component labeling (CCL) are performed in order to select a region of interest (ROI). After interpolating the selected ROI using bilinear interpolation, a location symbol pattern is detected as the same as for short-range detection. Finally, the symbol pattern is arranged by applying inverse perspective transformation to localize bar codes. Experimental results demonstrate that the proposed system successfully detects bar codes at two or three times longer distance than existing ones even at indoor environment.