• Journal of Sasang Constitutional Medicine
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• v.20 no.3
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• pp.70-81
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• 2008

1. Objective Recently we have known 'First Impression' is the major factor to check the review point for the classification of sasangin. And we want to find out the objected data contribute to dignosis of female sasang constitution using Sasangins Face. 2. Methods We analysed the datum collected by multi-center researchers in 2007-2008. And this study analysed the datum of the measurement of the face by 3D-AFRA (3-Dimensional Automatic Face Recognition Apparatus) and the items of impression by SDQ. We used chi-square test to define the relationship between the item and sasang constitutions. We used independent samples t - test with classifying measuring variables of the face. 3. Results and Conclusion We put out specific female sasangin's constitutional measuring variables of face. The measuring variables of count is Taeyangin 30point, Soyangin 15point, Taeumin 32point, Soeumin 21point. There is the need to accumulate more accurate pictures about sasangin's external shape.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.9 s.180
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• pp.2235-2245
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• 2000

The necessity of using rapid prototyping(RP) for short-run manufacturing is continuously driving a development of a cost-effective technique that will produce completely-finished quality parts in a very short time. To meet these demands, the improvements in production speed, accuracy, materials, aid cost are crucial. Thus, a new hybrid-RP system performing both deposition and machining in a station is proposed. For the new hybrid RP process to maintain the same degree of process automation as in currently available processes like SLA or FDNI, a sophisticated process planning system is developed. In the process planner, CAD models(STEP AP203) are partitioned into 3D manufacturable volumes called 'Ueposition feature segment"(DFS) after machining features called "machining feature segmenf'(MFS) are extracted from the initial CAD model. Once MFS and DFS are identified, the process planner arranges them into a chain of processes and automatically generates machining information for each DFS and MFS. The goal of this paper is to present a framework for a process planning system for hybrid RP processes and to outline the geometric algorithms involved in developing such an environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.6
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• pp.3023-3031
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• 2013

In this paper, we propose a robot control data generation system applying context aware mechanism in order to control the robot manipulator which automatically sorts parcels. The context aware mechanism generates intelligent information to control a robot using context data such as the parcel shape, weight, location and barcodes. The proposed system collects context data of the parcel and generates robot control data to pick up and drop parcels. Then a robot manipulator, which receives control data of picking-up and dropping, processes the automated sorting of parcels according to delivery persons and delivery routes. It will contribute not only to save much time and cost but also to reduce the industrial accidents.

• Design & Manufacturing
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• v.16 no.4
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• pp.46-51
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• 2022

The piercing process of creating holes in sheet metals for mechanical fastening generates high shear force. Real-time monitoring technology could predict tool damage and product defects due to this severe condition, but there are few applications for piercing high-strength aluminum. In this study, we analyzed the load signal to predict the punch's wear level during the process with a piezoelectric sensor installed piercing tool. Experiments were conducted on Al6061 T6 with a thickness of 3.0 mm using piercing punches whose edge angle was controlled by reflecting the wear level. The piercing load increases proportionally with the level of tool wear. For example, the maximum piercing load of the wear-shaped punch with the tip angle controlled at 6 degrees increased by 14% compared to the normal-shaped punch under the typical clearance of 6.7% of the aluminum piercing tool. In addition, the tool wear level increased compression during the down-stroke, which is caused by lateral force due to the decrease in the diameter of pierced holes. Our study showed the predictability of the wear level of punches through the recognition of changes in characteristic elements of the load signal during the piercing process.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.65-76
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• 2003

The analysis of cow body parameters is important to provide some useful information fur cow management and cow evaluation. Present methods give many stresses to cows because they are invasive and constrain cow postures during measurement of body parameters. This study was conducted to develop the stereo vision system fur non-invasive analysis of cow body features. Body feature parameters of 16 heads at two farms(A, B) were measured using scales and nineteen stereo images of them with walking postures were captured under outdoor illumination. In this study, the camera calibration and inverse perspective transformation technique was established fer the stereo vision system. Two calibration results were presented for farm A and fm B, respectively because setup distances from camera to cow were 510 cm at farm A and 630cm at farm B. Calibration error values fer the stereo vision system were within 2 cm for farm A and less than 4.9 cm for farm B. Eleven feature points of cow body were extracted on stereo images interactively and five assistant points were determined by computer program. 3D world coordinates for these 15 points were calculated by computer program and also used for calculation of cow body parameters such as withers height. pelvic arch height. body length. slope body length. chest depth and chest width. Measured errors for body parameters were less than 10% for most cows. For a few cow. measured errors for slope body length and chest width were more than 10% due to searching errors fer their feature points at inside-body positions. Equation for chest girth estimated by chest depth and chest width was presented. Maximum of estimated error fur chest girth was within 10% of real values and mean value of estimated error was 8.2cm. The analysis of cow body parameters using stereo vision system were successful although body shape on the binocular stereo image was distorted due to cow movements.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.43-50
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• 2018

The camera is a key element in image-based three-dimensional positioning, and camera calibration, which properly determines the internal characteristics of such a camera, is a necessary process that must be preceded in order to determine the three-dimensional coordinates of the object. In this study, a new methodology was proposed to determine interior orientation parameters of a camera semi-automatically without being influenced by size and shape of checkerboard for camera calibration. The proposed method consists of exterior orientation parameters estimation using quaternion, recognition of calibration target, and interior orientation parameter determination through bundle block adjustment. After determining the interior orientation parameters using the chessboard calibration target, the three-dimensional position of the small 3D model was determined. In addition, the horizontal and vertical position errors were about ${\pm}0.006m$ and ${\pm}0.007m$, respectively, through the accuracy evaluation using the checkpoints.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Journal of the Korean Society of Clothing and Textiles
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• v.18 no.4
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• pp.549-559
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• 1994

The purpose of this study was to study accumlated residual soils which may be one of the causes for yellowing of worn cloths. Wear and wash tests of white cotton undershirts were repeated at 30 households sellected at random over a period of 60 days. Laundry conditions were similar to home laundry habits in a fact-finding survey, using a powdery heavy duty detergent containing no enzymes or enzymes. The subjects in this study were survey of laundry actual condition, the undershirts from prior to and after the final washing was measured residual soils, $L^*a^*b^*$ value and mellowness index of CIE system. D3ta were analysed by simple correlation analysis of wear and wash cycle, residual soils, whiteness The results obtained were summarized as follows: 1. Using pattern of washing machine, Presoaking was no singinificant differnece in general characteristics of survey respondent. Laundry frequency was significant difference in income level, occupation of housewives whether or not. Use of cold and hot water was significant difference in residence shape. 2. The analyzed consequences of recognition and actual behavior in connection with laundry were found variables each other to have independence or not. 3. Amount of residual sebum soils is using non-enzyme detergent were much more than in using enzyme detergent, increased linearly with increase of the number of wear and wash cycles. 4. Residual protein soils with increase of the number wear and wash cycles less than in laundering more easy than sebum soils. Since accumulated residual sebum soils were much more than residual protein soils. 5. Increase of residual soils was raised mellowness index and diminshed whiteness. yellowness index of residual sebum soils was higher than protein soils. If increase of whiteness will be incresed, amount of residual sebum soils will be decreased sebum soils. Because amount of residual sebum soils much more than protein soils, yellowness index of residual sebum soils was more higher than that of protein soils.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.345-355
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• 2008

SIFT is popularly used in computer vision application such as object recognition, motion tracking, and 3D reconstruction among various shape descriptors. However, it is not easy to apply SIFT into the image similarity search as it is since it uses many high dimensional keypoint vectors. In this paper, we present a SIFT based image similarity search method using an edge image pyramid and an interesting region detection. The proposed method extracts keypoints, which is invariant to contrast, scale, and rotation of image, by using the edge image pyramid and removes many unnecessary keypoints from the image by using the hough transform. The proposed hough transform can detect objects of ellipse type so that it can be used to find interesting regions. Experimental results demonstrate that the retrieval performance of the proposed method is about 20% better than that of traditional SIFT in average recall.