學術產出-學位論文

題名 由地圖建構城市三維模型
Urban Buildings Modeling from Scanned Images
作者 賴易進
貢獻者 何瑁鎧
賴易進
關鍵詞 數位城市
文字辨識
特徵粹取
地圖向量化
日期 2006
上傳時間 17-九月-2009 13:59:02 (UTC+8)
摘要 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.
參考文獻 [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
描述 碩士
國立政治大學
資訊科學學系
93753025
95
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0093753025
資料類型 thesis
dc.contributor.advisor 何瑁鎧zh_TW
dc.contributor.author (作者) 賴易進zh_TW
dc.creator (作者) 賴易進zh_TW
dc.date (日期) 2006en_US
dc.date.accessioned 17-九月-2009 13:59:02 (UTC+8)-
dc.date.available 17-九月-2009 13:59:02 (UTC+8)-
dc.date.issued (上傳時間) 17-九月-2009 13:59:02 (UTC+8)-
dc.identifier (其他 識別碼) G0093753025en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/32660-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 93753025zh_TW
dc.description (描述) 95zh_TW
dc.description.abstract (摘要) 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。
zh_TW
dc.description.abstract (摘要) 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.
en_US
dc.description.tableofcontents 第一章 緒論 1
1.1前言 1
1.2問題描述 2
1.3研究動機 3
1.4論文章節架構 3
第二章 相關研究 5
第三章 系統架構 8
3.1 文字辨識 9
3.2 骨架粹取 9
3.3 節點決定 10
3.4 多邊形粹取 10
3.5 三維模型建構 10
第四章 地圖上的文字辨識 11
4.1 影像自動偵測及辨識文字系統 11
4.2 文字辨識 13
4.2.1 各點相連關係的建立 13
4.2.2 文字粹取 14
4.2.3 辨識文字 14
第五章 建物模型建構 16
5.1細化演算法 17
5.1.1 雜訊去除 17
5.1.2 相連線段偵測 17
5.1.3 細化 18
5.1.4 後處理 19
5.2 尋找節點 22
5.2.1 線段方向分析 22
5.2.2 線段長度分析 23
5.2.3 節點挑選 23
5.2.4 建立節點的相鄰關係 24
5.3 多邊形外廓粹取 26
5.3.1 線段的方向與旋轉方向 27
5.3.2 尋找順時針或逆時針方向的節點 29
5.3.3 建立建築物多邊形 30
5.4 建製地圖三維模型 32
第六章 實驗 35
6.1 文字粹取結果 36
6.2 地圖細化及節點找尋 37
6.3 多邊形粹取結果 39
6.4 城市三維模型 43
第七章 結論 47
7.1 結論 47
7.2 未來發展 48
參考資料: 49
zh_TW
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dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0093753025en_US
dc.subject (關鍵詞) 數位城市zh_TW
dc.subject (關鍵詞) 文字辨識zh_TW
dc.subject (關鍵詞) 特徵粹取zh_TW
dc.subject (關鍵詞) 地圖向量化zh_TW
dc.title (題名) 由地圖建構城市三維模型zh_TW
dc.title (題名) Urban Buildings Modeling from Scanned Imagesen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] Koushik Das, ”Desigh and Implementation of an Efficient Thinning Algorithm” Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, 2000.zh_TW
dc.relation.reference (參考文獻) [2] Victor Wu and R. Manmatha, “Document Image Clean-Up and Binarization” Proc. SPIE`98 Document Recognition V, p263-273, Jan. 1998.zh_TW
dc.relation.reference (參考文獻) [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, 2000zh_TW
dc.relation.reference (參考文獻) [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.zh_TW
dc.relation.reference (參考文獻) [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.zh_TW
dc.relation.reference (參考文獻) [6] D.Thibault and C.M Glod “Terrain Reconstruction from Contours by Skeleton Construction” Geoinformatica Volume 4 , Issue 4, p349 - 373 December 2000.zh_TW
dc.relation.reference (參考文獻) [7] Gold, C.M. and Snoeyink, J. “A one-step crust and skeleton extraction algorithm”, Algorithmica, 2001zh_TW
dc.relation.reference (參考文獻) [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), 2001zh_TW
dc.relation.reference (參考文獻) [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, 2003zh_TW
dc.relation.reference (參考文獻) [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, 1999zh_TW
dc.relation.reference (參考文獻) [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 1992zh_TW
dc.relation.reference (參考文獻) [12] T.Y.Zhang and C.Y.Suen,”Afast thinning algorithm for thinning digital patterns”, Comm. ACM 27, p236-239, 1984zh_TW
dc.relation.reference (參考文獻) [13] S.M. Smith, “Edge Thinning Used in the SUSAN Edge Detector” Defence Research Agency, Farnborough, Hampshire, GU14 6TD,1995zh_TW
dc.relation.reference (參考文獻) [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.zh_TW
dc.relation.reference (參考文獻) [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. 32/4zh_TW
dc.relation.reference (參考文獻) [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, 1998zh_TW
dc.relation.reference (參考文獻) [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, 1999zh_TW