• International Journal of CAD/CAM
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• v.5 no.1
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• pp.19-27
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• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.41-47
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• 2011

Processing of the raw LiDAR data requires the high-end processor, because data form is a vector. In contrast, if LiDAR data is converted into a regular grid pattern by filltering, that has advantage of being in a low-cost equipment, because of the simple structure and faster processing speed. Especially, by using grid data classification, such as Quadtree, some of trees and cars are removed, so it has advantage of modeling. Therefore, this study presents the algorithm for automatic extraction of ground points using Quadtree and refion growing method from LiDAR data. In addition, Error analysis was performed based on the 1:5000 digital map of sample area to analyze the classification of ground points. In a result, the ground classification accuracy is over 98%. So it has the advantage of extracting the ground points. In addition, non-ground points, such as cars and tree, are effectively removed as using Quadtree and region growing method.

• Horticultural Science & Technology
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• v.32 no.3
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• pp.340-345
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• 2014

Since the moisture content (MC) of growing medium closely related with the crop transpiration, the MC should be included to the environmental factors to be considered for irrigation control in soilless culture. The objective of this study was to analyze the transpiration of paprika plants using daily mean solar radiation (RAD) and vapor pressure deficit (VPD) as well as the growth of the plants at different MCs of rockwool growing media. The starting points of irrigation were controlled by a moisture sensor with minimum set points of 40%, 50%, and 60% of MCs. The canopy transpirations were measured for 80 to 120 days after transplanting and analyzed. The transpirations were well regressed with a combination of both RAD and VPD rather than daily mean RAD only under the controlled MCs. The transpiration at 60% MC was higher than those at 50% and 40% MCs. Leaf area, leaf fresh and dry weights at 60% MC were higher than those at 50% and 40% MCs while the number of leaves had no significant difference among the MCs. There were no significant differences in number of fruits and fruit size among all the MCs, while fruit weight was significantly lower at 40% MC than other treatments. Fresh and dry fruit yields were the highest at 60% MC. Therefore it was concluded that the transpiration was affected by the MC of rockwool growing medium and the minimum set point of 50-60% MC of rockwool growing medium gave better effects on the growth of the paprika plants.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.53.2-53.2
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• 2018

We perform seismological diagnostics of the physical parameters in umbral photospheres and G-band bright points. The technique is based on the theory of slow magneto-acoustic waves in a non-isothermally stratified photosphere with uniform vertical magnetic fields. For the seismology of sunspot umbrae, we calculate the weighted frequency of three-minute oscillations observed by SDO/HMI continuum and use it to estimate the Alfvn speed and plasma-beta, which range 7.5-10.5 km/s and 0.65-1.15, respectively. We identify and track bright points in the G-band movie by using a 3D region growing method. Then we apply the seismological diagnostics to the bright points in the Hinode/BFI Blue continuum. We will present the Alfvn speed and plasma-beta in the bright points.

• Magazine of the Korean Society of Agricultural Engineers
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• v.28 no.4
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• pp.41-48
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• 1986

This study was fulfilled by the weighing lysimeter method at the experimental farm of KonKuk University from April to June of 1986 to investgate the amount of evapotranspiration ( ET-lettuec )by the growing periods, evapotranspiration ratio, amount of watering per one time, days of intermission and soil moisture extraction pattern of the crisphead lettuce cultivated in the clay loam soil by different watering points of pFl.7, pF2.O, pF2.7. The results obtained are summar ized as follows : 1.The total evapotranspiration(ETlettuce) of the pFl.7 treatment plot was 358,9mm., 314.9mm in the pF2.O plot and 281.8mm in the pF2.7 plot, therefore the total ETlettuec increased with the difference of 33mm-44mm by the decrease of watering point. 2.The daily maximum ETlettuce by the watering points was 7.66mm, 6:54mm, 5.98mm, respectively in the last ten days of May, and the mean daily ETlettuce during the growing season by the watering points of pFl.7, pF2.O and pF2.7 was 5.44mm(384.5g), 4.77mm(337.2g) and 4.27mm(301.8g), respectively. 3.The evapotranspiration ratio showed maximum value in the middle of May which was the beginning of mid-season stage, and the mean evapotranspiration ratio during the total growing period was 1A7, 1.29, 1.15 by the watering points. 4.The days of watering intermission by the watering points of pFl.7, pF2.O and pF2.7 was 1.0day, 2.9days and 12.Sdays, respectively. 5.The yield of the crisphead lettuce by the watering treatments showed very high significance, and the pF2.O was confirmed as a optimum watering point. 6.The soil moisture extraction pattern(SMEP) of the pF2.0 treatment plot in the initial stage was 85.6% in the 1st and 2nd soil layer and 14.4% in the 3rd and 4th layer, and in the midseason stage, the moisture extraction proportion of the under layer accounted for 34.7%which showed that the root elongated to the lowest soil layer, and there was no difference of the SMEP between the mid-season and late-season stage. 7.The correlation coefficient between the ETlettuce and yield of lettuce by the three watering points was.739, which showed the significance of 5%.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.463-467
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• 2006

Several segmentation algorithms have been proposed for DTM generation or building modeling from airborne LiDAR data. Three components are important for accurate segmentation: (i) the adjacent relationship of n-nearest points or mesh, etc. (ii) the effective decision parameters of height, slope, curvature, and plane condition, (iii) grouping methods. In this paper, we created the topology of point cloud data using the contour tree and implemented the region-growing Terrain and non-terrain points were classified correctly in the segmented data, which can be used also for feature classification.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.612-624
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• 2005

In this paper, we propose a surface-based registration using a gaussian weighted distance map for PET-CT brain image fusion. Our method is composed of three main steps: the extraction of feature points, the generation of gaussian weighted distance map, and the measure of similarities based on weight. First, we segment head using the inverse region growing and remove noise segmented with head using region growing-based labeling in PET and CT images, respectively. And then, we extract the feature points of the head using sharpening filter. Second, a gaussian weighted distance map is generated from the feature points in CT images. Thus it leads feature points to robustly converge on the optimal location in a large geometrical displacement. Third, weight-based cross-correlation searches for the optimal location using a gaussian weighted distance map of CT images corresponding to the feature points extracted from PET images. In our experiment, we generate software phantom dataset for evaluating accuracy and robustness of our method, and use clinical dataset for computation time and visual inspection. The accuracy test is performed by evaluating root-mean-square-error using arbitrary transformed software phantom dataset. The robustness test is evaluated whether weight-based cross-correlation achieves maximum at optimal location in software phantom dataset with a large geometrical displacement and noise. Experimental results showed that our method gives more accuracy and robust convergence than the conventional surface-based registration.

• Journal of Korea Game Society
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• v.15 no.6
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• pp.131-140
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• 2015

The character is one of most important interest-element in role playing game genres since it shows the individuality. In general cases, game players allocate points to talent clauses that they choose. However, it is not easy to provide the suitable character-growing to players in generic system since the cases are too simple and based on just humans choices. In this paper, we propose the character growing system based on the player type inference module. Growth morphology is determined by player's behavior or type. The determination is based on petri-net. Our experimental results and analysis show that our proposed approach is suitable for character-growing system.

• Journal of International Society for Simulation Surgery
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• v.1 no.2
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• pp.75-79
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• 2014

Purpose The region growing has a critical problem that it often extract vessels with unexpected objects such as a bone which has a similar intensity characteristics to the vessel. We propose the new method to extract arterial vascular anatomy around the stomach from the CTA volume without the post-processing. Materials and Methods Our method, which is also based on the region growing, requires the two seed points from the use. I automatically extracts perigastric arteries using the adaptive region growing method and it does not need any post-processing. Results The three region growing based methods are used to extract perigastric arteries - the conventional region growings with restrict and loose thresholds each and the proposed method. The 3D visualization from the result of our method shows our method extracted the all required arteries for gastric surgery. Conclusion By extracting perigastric arteries using the proposed method, over-segmentation problem that unexpected anatomical objects such as a rib or backbone are also segmented does not occurs anymore. The proposed method does not need to sensitively determine the thresholds of the similarity function. By visualizing the result, the preoperative simulation of arterial vascular anatomy around the stomach can be possible.