• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.657-666
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• 2009

In GIS area, many line simplification algorithms are studied among generalization methods used for making the building data in the form of digital map from the original line data. On the other hand, there are few studies on the simplification algorithm considering the drawing rules of the digital map in Korea. In this paper, the line simplification algorithm based on the drawing rules is proposed as the methodology to create or update the building data of digital map by extracting the building outline from the CAD data used in construction. To confirm the usefulness of the algorithm, this algorithm and four other effective and general line simplification algorithms (e.g., Douglas-Peucker algorithm) are applied to the same building outlines. Then, the five algorithms are compared on five criteria, the satisfaction degree of the drawing rules, shape similarity, the change rate of the number of points, total length of lines, and the area of polygon. As a result, the proposed algorithm shows the 100% of satisfaction degree to the drawing rules. Also, there is little loss in four other mentioned criteria. Thus, the proposed algorithm in this paper is judged to be effective in updating the building data in digital map with construction drawings.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.4
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• pp.49-58
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• 2007

Hierarchical Mobile IPv6 (HMIPv6) has been proposed by Internet Engineering Task Force (IETF) to compensate for such problems as handover latency and signaling overhead in employing Mobile IPv6 (MIPv6). HMIPv6 supports micro-mobility within a domain and introduces a new entity, namely mobility anchor point (MAP) as a local home agent. However, HMIPv6 causes load concentration at a particular MAP and longer handover latency when inter-domain handover occurs. In order to solve such problems, this paper establishes a virtual domain (VD) of a higher layer MAP and proposes a MAP changing algorithm in which the routing path changes between mobile node (MN) and correspondent node(CN) according to the mobile position and the direction of the MN before inter-domain handover occurs. The proposed algorithm not only enables complete handover binding-update of the on-link care of address (LCoA) only when inter-domain handover occurs, but concentrated load of a particular MAP is distributed as well. This is because the MNs registered with higher layer MAP and lower layer MAP coexist in the VD. We simulate the performance of the proposed algorithm and compare with HMIPv6.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1939-1944
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• 2003

This paper presents a global path planning algorithm based on a visibility graph method, and applies additionally various constraints for constructing the reduced visibility graph. The modification algorithm for generating the rounded path is applied to the globally shortest path of the visibility graph using the robot size constraint in order to avoid the obstacle. In order to check the visibility in given 3D map data, 3D CAD data with VRML format is projected to the 2D plane of the mobile robot, and the projected map is converted into an image for easy map analysis. The image processing are applied to this grid map for extracting the obstacles and the free space. Generally, the tree size of visibility graph is proportional to the factorial of the number of the corner points. In order to reduce the tree size and search the shortest path efficiently, the various constraints are proposed. After short paths that crosses the corner points of obstacles lists up, the shortest path among these paths is selected and it is modified to the combination of the line path and the arc path for the mobile robot to avoid the obstacles and follow the rounded path in the environment. The proposed path planning algorithm is applied to the mobile robot LCAR-III.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.242-259
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• 2015

Three-dimensional video coding is one of the main challenges restricting the widespread applications of 3D video and free viewpoint video. In this paper, a novel fractal coding algorithm with motion-vector-field-based motion estimation for depth map sequence is proposed. We firstly add pre-search restriction to rule the improper domain blocks out of the matching search process so that the number of blocks involved in the search process can be restricted to a smaller size. Some improvements for motion estimation including initial search point prediction, threshold transition condition and early termination condition are made based on the feature of fractal coding. The motion-vector-field-based adaptive hexagon search algorithm on the basis of center-biased distribution characteristics of depth motion vector is proposed to accelerate the search. Experimental results show that the proposed algorithm can reach optimum levels of quality and save the coding time. The PSNR of synthesized view is increased by 0.56 dB with 36.97% bit rate decrease on average compared with H.264 Full Search. And the depth encoding time is saved by up to 66.47%. Moreover, the proposed fractal depth map sequence codec outperforms the recent alternative codecs by improving the H.264/AVC, especially in much bitrate saving and encoding time reduction.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.159-162
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• 2002

This paper presents a modified localization scheme of a mobile robot. When it navigates, the position error of a robot is increased and doesn't go to a goal point where the robot intends to go at the beginning. The objective of localization is to estimate the position of a robot precisely. Many algorithms were developed and still are being researched for localization of a mobile robot at present. Among them, a localization algorithm named continuous localization proposed by Schultz has some merits on real-time navigation and is easy to be implemented compared to other localization schemes. Continuous Localization (CL) is based on map-matching algorithm with global and local maps using only ultrasonic sensors for making grid maps. However, CL has some problems in the process of searching the best-scored-map, when it is applied to a mobile robot. We here propose fast and powerful map-matching algorithm for localization of a mobile robot by experiments.

• Journal of the Semiconductor & Display Technology
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• v.13 no.2
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.132-139
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• 2012

Presented in the paper is a procedure to extract simplified triangular mesh from a height map (terrain data). The proposed algorithm works directly on a height map that extracts a simplified triangular mesh. For the simplification, the paper employs an iterative method of edge contractions. To determine an edge to be contracted, the contraction cost of an edge is evaluated through the QEM method. Normally, an edge contraction will remove two triangles sharing the edge. Although the edge contraction can be implemented easily on a triangular mesh, it is not viable to implement the operation on a height map due to the irregular topology. To handle the irregular topology during the simplification procedure, a new algorithm is introduced.

• Journal of applied mathematics & informatics
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• v.9 no.2
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• pp.793-806
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• 2002

Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2840-2842
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• 2000

This paper describes sensor-based occupancy grid map construction method through complete coverage navigation algorithm in unknown environment. In this paper, we use the updated Baysian model for probabilistic grid map. For map construction, complete coverage navigation method in which mobile robot can navigate complete field through as short path as possible in unknown environment, is used. The computer simulations result show that map construction method using complete coverage algorithm is efficient.

• Journal of the Semiconductor & Display Technology
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• v.15 no.3
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• pp.67-71
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• 2016

This paper addresses a problem of defocus map recovery from single image. We describe a simple effective approach to estimate the spatial value of defocus blur at the edge location of the image. At first, we perform a re-blurring process using Gaussian function with input image, and calculate a gradient magnitude ratio with blurring amount between input image and re-blurred image. Then we get a full defocus map by propagating the blur amount at the edge location. Experimental result reveals that our method outperforms a reliable estimation of depth map, and shows that our algorithm is robust to noise, inaccurate edge location and interferences of neighboring edges within input image.