• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.127-135
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• 1999

Currently, many geographic information systems deal with only vector data. Therefore, handling raster data for various types of information is greatly needed. In this paper, we design and implement a raster processor which handles spatial information in a spatial object management system called Object Management system for Geospatial Application (OMEGA). We define the data structure of the raster information to be stored in the spatial object management system and implement it to a class library in order for use in making an application program. Furthermore, a query operation and related module is implemented to extract raster information. They are then imbedded in the query executer to process a query of the raster information. Simulation results are given.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.375-380
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• 2010

Most of previous algorithms of object boundary extraction have been studied for extracting the boundary of single object. However, multiple objects are much common in the real image. The proposed algorithm of extracting the boundary of each of multiple objects has two steps. In the first step, we propose the fast method using the outer and inner products; the initial contour including multiple objects is split and connected and each of new contours includes only one object. In the second step, an improved active contour model is studied to extract the boundary of each object included each of contours. Experimental results with various test images have shown that our algorithm produces much better results than the previous algorithms.

• Journal of Korea Multimedia Society
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• v.11 no.5
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• pp.623-632
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• 2008

In this paper, we used the color transfer function and the opacity transfer function for the internal 3D object visualization of an image volume data. In transfer function, creating values of between boundaries generally is ambiguous. We concentrated to extract boundary features for segmenting the visual volume rendering objects. Consequently we extracted an image gradient feature in spatial domain and created a multi-dimensional transfer function according to the GPU efficient improvement. Finally using these functions we obtained a good research result as an implementing object boundary visualization of the graphic hardware based 3D texture mapping.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.171-177
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• 2018

Recently there are many image datasets which has variety of data class and point to extract general features. But in order to this variety data class and point, deep learning model trained this dataset has not good performance in heterogeneous data feature local area. In this paper, we propose the structure which use sub-category and openset object detection methods to train more robust model, named multi-branch tree using ASSL. By using this structure, we can have more robust object detection deep learning model in heterogeneous data feature environment.

• The Journal of Korean Association of Computer Education
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• v.7 no.1
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• pp.27-35
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• 2004

Software documents consist of a number of objects and relationships between them, and structure of documents can be changed frequently. In the existing software version management models, changes in one object may be propagated to other objects unnecessarily. In this paper, we propose an efficient version management model for software objects based on history of operations applied to software objects. Operations applied to objects are recorded in the operation history, and those are used to retrieve versions of a document. Because versions of objects are stored and retrieved using the operation delta, it is not required to compare versions of a document to extract delta during check-in process. In addition, it can manage changes of structure of objects efficiently because it supports not only object creation, deletion, and update operation but also object move operation.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.229-235
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• 2011

To make a robust object tracking and identifying system for an intelligent robot and/or home system, heterogeneous sensor fusion between visible ray system and infrared ray system is proposed. The proposed system separates the object by combining the ROI (Region of Interest) estimated from two different images based on a heterogeneous sensor that consolidates the ordinary CCD camera and the IR (Infrared) camera. Human's body and face are detected in both images by using different algorithms, such as histogram, optical-flow, skin-color model and Haar model. Also the pose of human body is estimated from the result of body detection in IR image by using PCA algorithm along with AdaBoost algorithm. Then, the results from each detection algorithm are fused to extract the best detection result. To verify the heterogeneous sensor fusion system, few experiments were done in various environments. From the experimental results, the system seems to have good tracking and identification performance regardless of the environmental changes. The application area of the proposed system is not limited to robot or home system but the surveillance system and military system.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1089-1093
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• 2013

Depth extraction using the structured illumination method is popularly applied since it has the benefit of measuring the object without contact. With multiple spatial frequencies and phase-shifting techniques, it is possible to extract the depth of objects with large discontinuity. For applications such as 3D (Three Dimensional) displays, 3D information of the object is required and is useful if corresponding to each view of the display. For this purpose, hypercentric optics is appropriate to measure the depth information of an object with a large field of view that is applicable for a 3D display. By experiment, we present the feasibility for phase-shifting profilometry using hypercentric optics to obtain the depth information of an object with the field of view appropriate for a 3D display.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.5
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• pp.134-140
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• 2017

Shape-from-shading (SFS) or stereo vision algorithms can be utilized to measure the shape of an object with imaging techniques for effective sensing in non-contact measurements. SFS algorithms could reconstruct the 3D information from a 2D image data, offering relatively comprehensive information. Meanwhile, a stereo vision algorithm needs several feature points or lines to extract 3D information from two 2D images. However, to measure the size of an object with a freeform surface, the two algorithms need some additional information, such as boundary conditions and grids, respectively. In this study, a stereo vision scheme using the depth information obtained by shape-from-shading as patterns was proposed to measure the size of an object with a freeform surface. The feasibility of the scheme was proved with an experiment where the images of an object were acquired by a CCD camera at two positions, then processed by SFS, and finally by stereo matching. The experimental results revealed that the proposed scheme could recognize the size and shape of freeform surface fairly well.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.8 no.1
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• pp.15-22
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• 1990

The purpose of this study is to suggest possibility to analyze the three-dimensional positions of the whole surface of an object simultaneously and precisely by close-range photogrammetry. For this purpose, the geometry of network, namely imaging geometry and control configuration etc was considered, and then the whole surface of the object was analyzed by bundle adjustment through forma. lion of strip and block with which cover the whole surface of the object. As a result, we were able to prove possibility of the whole surface analysis of an object and to extract characteristics of accuracies in accordance with the number and configuration of control points. Also as desirable accuracies were able to be acquired even by employing configuration of only a few control point stationed on a limited surface, it is expected that the difficulties of control surveying will be able to be reduced considerably.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.1
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• pp.21-24
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• 2017

Passive millimeter wave (MMW) imaging penetrates clothing to detect concealed objects. The distances extraction to the concealed objects is critical for the security and defense. In this paper, we address a passive stereo 3 mm MMW imaging system to extract the longitudinal distance to the concealed object. The concealed object area is segmented and extracted by the k-means clustering algorithm with splitting initialization. The distance to the concealed object is estimated by the corresponding centers of the segmented objects. In the experimental two pairs (each pair for horizontal and vertical polarization) of stereo MMW images are obtained to estimate distances to concealed objects.