政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32660

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/32660

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政大典藏 > College of Informatics > Department of Computer Science > Theses > Item 140.119/32660

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/32660

Title:	由地圖建構城市三維模型 Urban Buildings Modeling from Scanned Images
Authors:	賴易進
Contributors:	何瑁鎧賴易進
Keywords:	數位城市文字辨識特徵粹取地圖向量化
Date:	2006
Issue Date:	2009-09-17 13:59:02 (UTC+8)
Abstract:	在資訊科技爆炸的時代，所有的資料都要求能數位化，以便利用資訊科技對數位資料進行分析、整理與應用。對於都市規劃而言，建立數位城市模型即成為目前的重要課題之一。建立數位城市模型中間最困難的步驟之一，在於處理並數位化古老的紙本地籍資料與建築物平面圖或手繪建築物之地圖，然後進行資訊整合，以建立基本的城市三度空間模型，進而利用更精準的測量技術，來建立精確的數位城市模型。然而要以人工處理並將上述資料數位化來製作基本的三度空間模型，秏時費工且成本太高。有鑑於此，本篇論文提出一套自動化的處理方法，針對附有樓層高度的紙本建築地圖或手繪地圖進行自動化處理，從而建立基本的三度空間模型，作為建立數位城市模型的初步處理。我們先利用文字辨識的技術對建築物進行分析、擷取並判斷地圖中屬於建築物高度的文字資料。其次利用不同的演算法，對地圖進行細化及骨架粹取，並找出地圖上組成建築物的關鍵節點，然後對節點分群，以區分並判斷不同的建築物，進而建立地圖上各個建築物的平面模型圖。最後將每棟建築物的高度資料及其相對應的平面模型圖加以整合，自動產生該地圖的三度空間模型。我們隨機選取一張台北地區之建築平面圖以及學校平面圖來檢驗我們提出的方法，測試的結果顯示，我們的方法都能成功的將這些平面圖，自動建立出原圖基本的三度空間模型，可以作為未來建立城市數位模型之參考。 In the era of information explosion, digital archiving every piece of information becomes a must in order to organize, process, and analyze this information and make further use of the information. Hence, constructing a cyber city model is one of the major issues in urban planning. One of the most difficult steps in constructing a cyber city model is to process and digitize the ancient cadastral information as well as the architecture sketches or the hand drawing maps. By combining this information, we could construct an early stage three dimensional model for the city that would help us in constructing the final model for the cyber city. However, manually processing this information is not cost effectively and automatic processing them might reduce the construction cost dramatically. In this paper, we propose an automatic processing mechanism that could digitize the architecture sketches or the hand drawing maps automatically. Our mechanism will produce an early stage three dimensional model for the specified area that will eventually lead to the construction of a more accurate three dimensional model for the entire city. After the sketches or the maps were scanned, as bitmap images, into the computer, we start with analyzing the architecture sketches and extract the elevation information using traditional methods of character recognition. Then, we use various algorithms to thinning and to extract the skeleton of the image. The critical nodes of each building in the images were identified, isolated, and used to construct the base of each building in a planar diagram. Finally, the elevation information is used along with the planar diagram just constructed to generate an early stage three dimension model for the specified area. We randomly choose an architecture sketch of Taipei City and our campus map to verify our mechanism. The results show that our method could produce the corresponding three dimensional models successfully. These models could be used and help us to construct a more accurate three dimensional model for the entire city.
Reference:	[1] Koushik Das, ”Desigh and Implementation of an Efficient Thinning Algorithm” Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, 2000. [2] Victor Wu and R. Manmatha, “Document Image Clean-Up and Binarization” Proc. SPIE`98 Document Recognition V, p263-273, Jan. 1998. [3] Luyang Li, George Nagy, Ashok Samal, Sharad Seth, and Yihong Xu, “Integrated Text and Line-Art Extraction from a Topographic Map” International Jounal on Document Anysis and Recognition, vol 2: p177-185, 2000 [4] Gold, C.M., J. Nantel, and W. Yang, “ Outside-in: an alternative approach to forest map digitizing.” International Journal of Geographical Information Systems, v. 10, no. 3, p291-310,1996. [5] Philippe Dosch, and Ge´rald Masini “Urban Environment Modelling by Fusion of a Cadastral Map and a Digital Elevation Model” 10th Scandinavian Conference on Image Analysis - SCIA` 97, Lappeenranta, Finland, p431-437, June 1997. [6] D.Thibault and C.M Glod “Terrain Reconstruction from Contours by Skeleton Construction” Geoinformatica Volume 4 , Issue 4, p349 - 373 December 2000. [7] Gold, C.M. and Snoeyink, J. “A one-step crust and skeleton extraction algorithm”, Algorithmica, 2001 [8] Christophe Vestri and Fr´ed´eric Devernay “Using Robust Methods for Automatic Extraction of Buildings” Computer Vision and Pattern Recognition, Hawaii, USA, p. 1-133-8, vol. 1.2 (d) (e) (f), 2001 [9] Sayaka Suzuki, “Recreating the Past City Model of Historical Town Kawagoe from Antique Map”, International Archives of Photogrammetry and Remote Sensing , Vol.XXXIV-5/W10, ISSN 1682-1777, Vulpera, 2003 [10] Victor Wu, Raghavan Manmatha, and Edward M. Riseman, “TextFinder: An Automatic System to Detect and Recognize Text In Images” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, NO. 11, 1999 [11] Louisa Lam, Seong-Whan Lee, and Ching Y. Suen, “Thinning Methodologies -A Comprehensive Survey” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, NO. 9, september 1992 [12] T.Y.Zhang and C.Y.Suen,”Afast thinning algorithm for thinning digital patterns”, Comm. ACM 27, p236-239, 1984 [13] S.M. Smith, “Edge Thinning Used in the SUSAN Edge Detector” Defence Research Agency, Farnborough, Hampshire, GU14 6TD,1995 [14] Guibas L., D. Salesin, and J. Stolfi “Epsilon geometry: building robust algorithms from imprecise computations.” Proc. 5th Annual ACM Symposium on Computational Geometry, p208-217, 1989. [15] L. Rognant, S. Goze, and J.G Planès.” Triangulated Digital Elevation Model: Definition of a New Representation.”, ISPRS Commission iv Symposium on GIS - between visions and applications,stuttgart, vol. 32/4 [16] Norbert Haala, Claus Brenner, and Karl-Heinrich Anders,” 3D Urban GIS from Laser Altimeter and 2D Map Data”, International Archives of Photogrammetry and Remote Sensing, vol. 32, part 3/1, p339-346, 1998 [17] L.Rognant, J.M. Chassery, S. Goze, and J.G Planès.” The Delaunay Constrained Triangulation :The Delaunay Stable Algorithms”, Proceedings of the 1999 International Conference on Information Visualisation, p147, 1999
Description:	碩士國立政治大學資訊科學學系 93753025 95
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0093753025
Data Type:	thesis
Appears in Collections:	[Department of Computer Science ] Theses

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