• Journal of Environmental Impact Assessment
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• v.15 no.4
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• pp.271-277
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• 2006

In this study, we investigated the applicable plan of GIS on the environmental impact assessment of 60 Hz Powerline. So we assessed distance data based on calculations by use of 2D and 3D Geographical information systems(GIS) and distance data based on measurements on 1: 5000 maps accord with on site distance measurements to use input data for calculating magnetic field. One hundred eight of the on site measured addresses were selected from residences. The data were achieved by measuring the distance between residence and power line on maps with scales of 1: 5000. The digital map was obtained from National Geographic Information Institute with scales of 1: 5000, and we made 2D and 3D map. Correlation analyses were performed for statistical analyses. For the 3D GIS versus on site comparison of different exposure categories, 70 of 108 measurements were assigned to the correct category. Similarly for 2D GIS versus on site comparison, 71 of 108 were correctly categorized. When comparing map measurement with on site measurement, 62 of 108 were correctly categorized. When the correlation analysis was performed, best correlation was found between 3D GIS and on site measurements with r = 0.84947 (p<0.0001). The correlation between map and on site measurement yielded an r of 0.76517 (p<0.0001). Since the GIS measurements and map measurement were made from the center point in the building and the on site measurements had to be made from the closest wall on the building, this might introduce and additional error in urban areas. The difference between 2D and 3D calculations were resulted from the height of buildings.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.101.1-101
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• 2001

This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

• 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 the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.36-48
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• 2010

This paper is concerned with stereo vision-based approach to detect obstacles and to generate the path of destination from the start. The hexapod robot in the experiment is cable of walking by legs and driving by wheels simultaneously. The hexapod robot operates under the driving mode normally, and it changes driving mode to walking mode to overcome obstacles using its legs. Disparity map, which is the correlation between two images taken by stereo camera, is employed for calculation of the distance between the robot and obstacles. When the obstacles information is extracted from the disparity map, the potential field algorithm is applied to create the obstacle-avoidance path. Simulator, based on OpenGL, is developed to generate the graphical path, and the experimental results are shown for the verification of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2657-2675
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• 2013

A novel neighbor selection-based fingerprinting algorithm using matrix correlation (MC) for Wi-Fi localization is presented in this paper. Compared with classic fingerprinting algorithms that usually employ a single received signal strength (RSS) sample, the presented algorithm uses multiple on-line RSS samples in the form of a matrix and measures correlations between the on-line RSS matrix and RSS matrices in the radio-map. The algorithm makes efficient use of on-line RSS information and considers RSS variations of reference points (RPs) for localization, so it offers more accurate localization results than classic neighbor selection-based algorithms. Based on the MC algorithm, an error estimation method using artificial neural network is also presented to fuse available information that includes RSS samples and localization results computed by the MC algorithm and model the nonlinear relationship between the available information and localization errors. In the on-line phase, localization errors are estimated and then used to correct the localization results to reduce negative influences caused by a static radio-map and RP distribution. Experimental results demonstrate that the MC algorithm outperforms the other neighbor selection-based algorithms and the error estimation method can reduce the mean of localization errors by nearly half.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.695-701
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• 2008

In this paper, we propose the efficient Doppler removal method using map-based partial-time common intermediate frequency removal technique. In the proposed algorithm, the 2-stage carrier removal process was used. First, the component of common intermediate frequency is removed. Next the component of Doppler was removed with averaging and approximation. For the evaluation of the proposed algorithm, The real-time software GPS L1 C/A-code receiver was implemented. When the proposed algorithms are used, 12 tracking channels with 3 track arm(early, prompt, late) is operated real-time on PC using a Intel Pentium-III 1.0GHz CPU. Also, the requirement of memory was less than 2Mbytes. The real-time software GNSS receiver using the proposed algorithms provides the navigation solution with below 10 meter rms error. Especially, in spited of using the various approximations for implementing the algorithms, the high sensitivity capability (able to track the weak signal with -159dBm) was achieved.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.1-10
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• 2018

Wide-area monitoring of tree-related high impedance fault (THIF) efficiently contributes to increase reliability of large-scaled network, since the failure to early location of them may results in critical lines tripping and consequently large blackouts. In the first place, this wide-area monitoring of THIF requires managing the placement of sensors across large power grid network according to THIF detection objective. For this purpose, current paper presents a framework in which sensors are distributed according to a predetermined risk map. The proposed risk map determines the possibility of THIF occurrence on every branch in a power network, based on electrical conductivity of trees and their positions to power lines which extracted from spectral data. The obtained possibility value can be considered as a weight coefficient assigned to each branch in sensor placement problem. The next step after sensors deployment is to on-line monitor based on moving data window. In this on-line process, the received data window is evaluated for obtaining a correlation between low frequency and high frequency components of signal. If obtained correlation follows a specified pattern, received signal is considered as a THIF. Thereafter, if several faulted section candidates are found by deployed sensors, the most likely location is chosen from the list of candidates based on predetermined THIF risk map.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1647-1658
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• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• Journal of Environmental Impact Assessment
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• v.22 no.5
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• pp.455-466
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• 2013

The aim of this study is to seek application plans of National Ecosystem Survey database based on comparison and examination of feasible analysis methods for distribution characteristics of alien plants. In order to set up a correlation analysis method between alien plants and environmental factors, we had reviewed the 3rd National Ecosystem Survey guide book and consequently, two kinds of analysis method were tested. One was 1/25,000 scale map boundary based analysis and the other was representative mountain area based analysis. In this study we restricted the research area to select reliable surveyed database from whole "2011 National Ecosystem Survey flora database" according to two major criteria. First, an area defined by 1/25,000 scale map boundary and representative mountain area where the number of surveyed flora records should be within top 20%. Second, land cover map should also be built up inside that area. As a result, 25 map boundaries and 25 representative mountain areas were extracted to be analyzed. To limit a boundary for every representative mountain area we had analyzed distribution of environmental factors around that area by manual inspection with SPOT-5 remote sensed satellite image then designated 3km buffer zone from each alien plant location in that area. After then, naturalized index (NI) and urbanized index (UI) was calculated and correlations analysis was carried out. With the result of correlation analysis by map boundary only agricultural land area showed significant value of r (0.4~0.6, correlated) and the rest of factors did not. In the case of representative mountain area, the result showed that agricultural land, road and forest area showed significant value of r (0.6~0.8, highly correlated) which was corresponding to existing researches. Therefore, representative mountain area based method is preferable when using the alien plants database of National Ecosystem Survey for species distribution analysis. And also, considering the way of database utilization is strongly suggested at the first stage of survey planning for promoting active use of national ecosystem survey database.