• Title/Summary/Keyword: Map registration

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Co-registration of Airborne Photo, LIDAR data, and Digital Map for construction of 3D Terrain Map - Using Linear Features (3차원 지형지도 작성을 위한 항공사진, LIDAR 데이터, 수치지도의 Co-registration 기법 연구 - Linear feature를 기반으로)

  • Lee Jae-Bin;Kim Ji-Young;Park Seung-Ryong;Yu Ki-Yun
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2006.04a
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    • pp.235-241
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    • 2006
  • The demand of 3D terrain mapping techniques is increasing in many application fields such as CNS(Car Navigation System), web service system, DMB(Digital Multimedia Broadcasting) systems and etc To construct a 3D terrain map, it is a pre-requite step that register data collected from different surveying sources. This Paper Present the methodology to register airborne photo, LIDAR data, and digital map, which are major data sources to create a 3D terrain mao. For this purpose, we developed the generally applicable algorithm that uses linear features to register airborne photos and digital maps to LIDAR data. The algorithm explicitly formulates step-by-step methodologies to establish observation equations for transformation. The results clearly demonstrate the proposed algorithm is appropriate to register these data sources.

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CO-REGISTRATION OF KOMPSAT IMAGERY AND DIGITAL MAP

  • Han, Dong-Yeob;Lee, Hyo-Seong
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.11-13
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    • 2008
  • This study proposes the method to use existing digital maps as one of the technologies to exclude individual differences that occur in the process of manually determining GCP for the geometric correction of KOMPSAT images and applying it to the images and to automate the generation of ortho-images. It is known that, in case high-resolution satellite images are corrected geometrically by using RPC, first order polynomials are generally applied as the correction formula in order to obtain good results. In this study, we matched the corresponding objects between 1:25,000 digital map and a KOMPSAT image to obtain the coefficients of the zero order polynomial and showed the differences in the pixel locations obtained through the matching. We performed proximity corrections using the Boolean operation between the point data of the surface linear objects and the point data of the edge objects of the image. The surface linear objects are road, water, building from topographic map.

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3D Multi-floor Precision Mapping and Localization for Indoor Autonomous Robots (실내 자율주행 로봇을 위한 3차원 다층 정밀 지도 구축 및 위치 추정 알고리즘)

  • Kang, Gyuree;Lee, Daegyu;Shim, Hyunchul
    • The Journal of Korea Robotics Society
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    • v.17 no.1
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    • pp.25-31
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    • 2022
  • Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

A Study on the Action Plan for the Building Registration on the Cadastral Map (지적도상 건축물 등록을 위한 실행방안 연구)

  • Jeong, Dong Hoon;Bae, Sang Keun;Kim, Jin
    • Spatial Information Research
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    • v.22 no.5
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    • pp.77-85
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    • 2014
  • As In spite of a close relationship between the land and the building administration, the registration information have been managed separately, because of the different department and the different working area as a national office. To record and manage the exact location of the building within the land we should oblige to submit a status survey results and also register them on the cadastral map. Even now we should make a business cooperation system by building a co-construction of information. The purposes of this study are to suggest ways to improve the legal system for the exact registration of a building on the cadastral map and to look for ways to increase the confidence of building information by reducing the inconvenience of the people through the analysis of a current building administration.

Co-registration of PET-CT Brain Images using a Gaussian Weighted Distance Map (가우시안 가중치 거리지도를 이용한 PET-CT 뇌 영상정합)

  • Lee, Ho;Hong, Helen;Shin, Yeong-Gil
    • 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.

MAP Scenarios and Protocol Stack in IMT-2000 MSC (IMT-2000 MSC MAP 시나리오 및 프로토콜 스택)

  • 박현화
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.257-260
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    • 1998
  • In this paper, we describe an IMT-2000 system architecture, a protocol stack, and basic MAP scenarios(e.g., registration, call delivery) based on the IS-41 and IS-41 and IS-751. This paper focuses on the MAP scenarios to support the IMSI which is defined for the global roaming between GSM and IS-41 Networks through the Family of System approach. This paper also deals with the design of the MAP protocol stack transported over the ATM networks and introduces the software structure of MAP in IMT-2000 MSC.

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Map registration of building construction plan drawing with shape matching of cadastral parcel polygon (필지 객체의 형상 정합을 이용한 건물 설계도면의 좌표 등록)

  • Huh, Yong;Yu, Kiyun;Yang, Sungchul
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.31 no.3
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    • pp.193-198
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    • 2013
  • This study proposed a map registration method of a building construction plan drawing with shape matching of cadastral parcel polygon. In general, the drawing contains information about a building boundary and a cadastral parcel boundary. The shape of this cadastral parcel boundary should be same as that of the corresponding parcel polygon object in the KLIS continuous cadastral map. Thus, shape matching between two parcel boundary polygons from the drawing and cadastral map could present transformation parameters. Translation and scaling amounts could be obtained by difference of centroid coordinates and area ratio of the polygons, respectively. Rotation amount could be obtained by the rotation that presents the minimum Turning function dissimilarity of the polygons. The proposed method was applied for building construction plan drawings in eAIS for an urban area in Suwon. To assess positional accuracy of map registration, building polygons in registered drawings and aerial photos were compared. According to the accuracy of the cadastral map which is the reference dataset of the proposed method, the RMSE of corresponding buildings' corners was 0.95m and 2.37m in new and old urban areas, respectively.

Wavelet Transform based Image Registration using MCDT Method for Multi-Image

  • Lee, Choel;Lee, Jungsuk;Jung, Kyedong;Lee, Jong-Yong
    • International Journal of Internet, Broadcasting and Communication
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    • v.7 no.1
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    • pp.36-41
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    • 2015
  • This paper is proposed a wavelet-based MCDT(Mask Coefficient Differential and Threshold) method of image registration of Multi-images contaminated with visible image and infrared image. The method for ensure reliability of the image registration is to the increase statistical corelation as getting the common feature points between two images. The method of threshold the wavelet coefficients using derivatives of the wavelet coefficients of the detail subbands was proposed to effectively registration images with distortion. And it can define that the edge map. Particularly, in order to increase statistical corelation the method of the normalized mutual information. as similarity measure common feature between two images was selected. The proposed method is totally verified by comparing with the several other multi-image and the proposed image registration.

Development of the Multi-Parametric Mapping Software Based on Functional Maps to Determine the Clinical Target Volumes (임상표적체적 결정을 위한 기능 영상 기반 생물학적 인자 맵핑 소프트웨어 개발)

  • Park, Ji-Yeon;Jung, Won-Gyun;Lee, Jeong-Woo;Lee, Kyoung-Nam;Ahn, Kook-Jin;Hong, Se-Mie;Juh, Ra-Hyeong;Choe, Bo-Young;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.21 no.2
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    • pp.153-164
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    • 2010
  • To determine the clinical target volumes considering vascularity and cellularity of tumors, the software was developed for mapping of the analyzed biological clinical target volumes on anatomical images using regional cerebral blood volume (rCBV) maps and apparent diffusion coefficient (ADC) maps. The program provides the functions for integrated registrations using mutual information, affine transform and non-rigid registration. The registration accuracy is evaluated by the calculation of the overlapped ratio of segmented bone regions and average distance difference of contours between reference and registered images. The performance of the developed software was tested using multimodal images of a patient who has the residual tumor of high grade gliomas. Registration accuracy of about 74% and average 2.3 mm distance difference were calculated by the evaluation method of bone segmentation and contour extraction. The registration accuracy can be improved as higher as 4% by the manual adjustment functions. Advanced MR images are analyzed using color maps for rCBV maps and quantitative calculation based on region of interest (ROI) for ADC maps. Then, multi-parameters on the same voxels are plotted on plane and constitute the multi-functional parametric maps of which x and y axis representing rCBV and ADC values. According to the distributions of functional parameters, tumor regions showing the higher vascularity and cellularity are categorized according to the criteria corresponding malignant gliomas. Determined volumes reflecting pathological and physiological characteristics of tumors are marked on anatomical images. By applying the multi-functional images, errors arising from using one type of image would be reduced and local regions representing higher probability as tumor cells would be determined for radiation treatment plan. Biological tumor characteristics can be expressed using image registration and multi-functional parametric maps in the developed software. The software can be considered to delineate clinical target volumes using advanced MR images with anatomical images.

Image Registration for Cloudy KOMPSAT-2 Imagery Using Disparity Clustering

  • Kim, Tae-Young;Choi, Myung-Jin
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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    • pp.287-294
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    • 2009
  • KOMPSAT-2 like other high-resolution satellites has the time and angle difference in the acquisition of the panchromatic (PAN) and multispectral (MS) images because the imaging systems have the offset of the charge coupled device combination in the focal plane. Due to the differences, high altitude and moving objects, such as clouds, have a different position between the PAN and MS images. Therefore, a mis-registration between the PAN and MS images occurs when a registration algorithm extracted matching points from these cloud objects. To overcome this problem, we proposed a new registration method. The main idea is to discard the matching points extracted from cloud boundaries by using an automatic thresholding technique and a classification technique on a distance disparity map of the matching points. The experimental result demonstrates the accuracy of the proposed method at ground region around cloud objects is higher than a general method which does not consider cloud objects. To evaluate the proposed method, we use KOMPSAT-2 cloudy images.