• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.169-180
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• 2019

Shorelines should be extracted with consistency because they are the reference for determining the shape of a country. Even in the same area, inconsistent minimum vertex intervals cause inconsistencies in the coastline length, making it difficult to acquire reliable primary data for national policy decisions. As the shoreline length cannot be calculated consistently for shorelines produced by determining the arbitrary distance between points below 1m, a methodology to calculate consistent shoreline length using the minimum vertex interval is proposed herein. To compare our results with the shoreline length published by KHOA(Korea Hydrographic and Oceanographic Agency) and analyze the change in shoreline length according to the minimum vertex interval, target sites was selected and the grid overlap of the shoreline was determined. Based on the comparison results, minimum grid sizes and the minimum vertex interval can be determined by deriving a polynomial function that estimates minimum grid sizes for determining consistent shoreline lengths. By comparing public shoreline lengths with generalized shoreline lengths using various grid sizes and by analyzing the characteristics of the shoreline according to vertex intervals, the minimum vertex intervals required to achieve consistent shoreline lengths could be estimated. We suggest that the minimum vertex interval methodology by quantitative evaluation of the determined grid size may be useful in calculating consistent shoreline lengths. The proposed method by minimum vertex interval determination can help derive consistent shoreline lengths and increase the reliability of national shorelines.

• Journal of the Korea Computer Graphics Society
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• v.5 no.2
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• pp.1-7
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• 1999

We present an algorithm to reconstruct a pipe surface from a set of unorganized points. A pipe surface is defined by a spine curve and a radius of a swept sphere. In this paper, by using the shrinking and moving least-squares methods, a point cloud is reduced to a thin curve-like point set that can be easily approximated with a spine curve of a pipe surface. The distance between a point in the thin point cloud and a corresponding point in the original point set represents the radius of a swept sphere of a pipe surface.

• Journal of Bio-Environment Control
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• v.24 no.3
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• pp.210-216
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• 2015

Purpose of this study was a development of an image processing algorithm to recognize paprika and acquire it's 3D coordinates from stereo images to precisely control an end-effector of a paprika auto harvester. First, H and S threshold was set using HSI histogram analyze for extracting ROI(region of interest) from raw paprika cultivation images. Next, fundamental matrix of a stereo camera system was calculated to process matching between extracted ROI of corresponding images. Epipolar lines were acquired using F matrix, and $11{\times}11$ mask was used to compare pixels on the line. Distance between extracted corresponding points were calibrated using 3D coordinates of a calibration board. Non linear regression analyze was used to prove relation between each pixel disparity of corresponding points and depth(Z). Finally, the program could calculate horizontal(X), vertical(Y) directional coordinates using stereo camera's geometry. Horizontal directional coordinate's average error was 5.3mm, vertical was 18.8mm, depth was 5.4mm. Most of the error was occurred at 400~450mm of depth and distorted regions of image.