• 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.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.3
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• pp.29-40
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• 2012

The method regarding obtaining various kinds of attribute data of spatial information, including that of digital map, is normally restricted to Geographic survey that deals with in-field surveys. Geographic surveying for drawing digital map, however, require much effort due to the fact that a surveyor has to characterize geographic features individually in the field. Not only does the Geographic survey cover large area, but also its need for manual drawing and surveying using Draft map makes it more expensive and time-consuming. Though some recent Geographic surveys take advantage of MMS(Mobile Mapping System) to collect computerized information, there are inevitable limits in creating digital map with such data. This research will analyze the problems in current Geographic surveys and suggest adequate methods and standards for Geographic surveys by researching the methods of domestic/international service organizations that deal with establishing spatial information. This study therefore will aim to enhance the efficiency of creating digital map and Geographic survey, which would ultimately maximize the applicability of pan-national digital map by improving reliability of digital map and upgrading the utilizability of Geographic survey data.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.483-497
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• 2023

Depth estimation is one of the most complicated and difficult problems to deal with in the light field. In this paper, a compound attention convolutional neural network (CAttNet) is proposed to extract depth maps from light field images. To make more effective use of the sub-aperture images (SAIs) of light field and reduce the redundancy in SAIs, we use a compound attention mechanism to weigh the channel and space of the feature map after extracting the primary features, so it can more efficiently select the required view and the important area within the view. We modified various layers of feature extraction to make it more efficient and useful to extract features without adding parameters. By exploring the characteristics of light field, we increased the network depth and optimized the network structure to reduce the adverse impact of this change. CAttNet can efficiently utilize different SAIs correlations and features to generate a high-quality light field depth map. The experimental results show that CAttNet has advantages in both accuracy and time.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.1-12
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• 2023

To make semiconductor chips, a number of complex semiconductor manufacturing processes are required. Semiconductor chips that have undergone complex processes are subjected to EDS(Electrical Die Sorting) tests to check product quality, and a wafer bin map reflecting the information about the normal and defective chips is created. Defective chips found in the wafer bin map form various patterns, which are called defective patterns, and the defective patterns are a very important clue in determining the cause of defects in the process and design of semiconductors. Therefore, it is desired to automatically and quickly detect defective patterns in the field, and various methods have been proposed to detect defective patterns. Existing methods have considered simple, complex, and new defect patterns, but they had the disadvantage of being unable to provide field engineers the evidence of classification results through deep learning. It is necessary to supplement this and provide detailed information on the size, location, and patterns of the defects. In this paper, we propose an anomaly detection framework that can be explained through FCDD(Fully Convolutional Data Description) trained only with normal data to provide field engineers with details such as detection results of abnormal defect patterns, defect size, and location of defect patterns on wafer bin map. The results are analyzed using open dataset, providing prominent results of the proposed anomaly detection framework.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.173-183
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• 2020

In the midst of the aging of underground facilities in urban areas and anxiety about road excavation safety accidents, the Ministry of Land, Infrastructure and Transport began to build Underground Geospatial Infomation Map from 2015 as part of the 「ground subsidence prevention measures」 and efficient use of underground spaces. So, the scope is spreading every year. The current Underground Geospatial Infomation Map information is web-based and is operated in a desktop environment, so it is true that there are some limitations in its use in a field environment such as an excavation construction site. The Underground Geospatial Infomation Map, built and operated in a web-based environment, is a large-scale 3D data. Therefore, in order to service by transmitting data to the field without delay, it is necessary to lighten the Underground Geospatial Infomation Map data. In addition, the current Underground Geospatial Infomation Map is not unified in data formats such as 3DS and COLLADA, and the coordinate system method is also different in relative coordinates and absolute coordinates. In this study, by analyzing domestic and overseas prior research and technical use cases, a mobile Underground Geospatial Infomation Map data format and a lightweight method were presented, and a technology development was conducted to create a mobile underground space integration map in the presented format. In addition, the weight reduction rate was tested by applying 3D data compression technology so that data can be transmitted quickly in the field, and technology was developed that can be used by decompressing 3D data compressed in the field. finally, it aims to supplement the technology experimentally developed in this study and conduct additional research to produce it as software that can be used in the excavation site and use it.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.1
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• pp.145-151
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• 2014

This paper proposes an image haze removal algorithm for a single image. The conventional Dark Channel Prior(DCP) algorithm estimates a transmission map using the dark information in an image, and the haze regions are then detected using a matting algorithm. However, since the DCP algorithm uses block-based processing, block artifacts are invariably formed in the transmission map. To solve this problem, the proposed algorithm generates a modified transmission map using a Hidden Markov Random Field(HMRF) and Expectation-Maximization(EM) algorithm. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.307-308
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• 1998

In this paper, we describe a field measurement technique using multiple gradient echo method. For this purpose, 3 differential phase map is used between two images obtained in a single scan. The phase map is further processed to unfold phase folding (2n $\pi$). The inhomogeneity map is used to correct image distortion along readout gradient direction. Some experimental results obtained at 1.0 Tesla whole body MR system are shown with the proposed technique.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.57-68
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• 1999

In case of topographic information construction it is most important as basemap determines the success or failure of GIS It is argument that digitizing works of basemap are divided by NGIS and PBLIS. So, it have to accompany the combination and application of cadastral information for constructing a usful basemap. In this study, we generated ortho image map using 1:5,000 aerial-photography image, present the comparative analysis for the overlay accuracy and map revision of topographic and cadastral information using ortho image map to base map. So, we present application schemes for land use, environment, and city planning field as well as union database by overlaying of image map and cadastral information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.115-121
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• 2011

The flight information visualization of the aircraft is the system which is widely used to the threat against low altitude tasks and terrain altitude. But, it is difficult to implement the system because of restrictions that GPS data and huge geographic information should be stored. In this paper, it proposes economic DMM (Digital Moving Map) system for flight information visualization from open-source-base. First, the flight information is transferred from X-Plane through UDP and then demonstrated on the DMM system. In the proposed DMM system, flight information is visualized on the map information downloaded from an ArcGIS Map server using the mapping data between the present altitude of the aircraft and the terrain altitude. The result of this paper could be used an economic tool in the field of flight information visualization and the game algorithm research.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.