簡易檢索 / 詳目顯示

研究生: 黃柏翔
論文名稱: 點陣文字和圖形之漸變演算法
Morphing Bitmap Font Characters and Images
指導教授: 潘雙洪
口試委員: 潘雙洪
陳朝欽
黃世強
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Computer Science
論文出版年: 2014
畢業學年度: 102
語文別: 英文
論文頁數: 79
中文關鍵詞: 點陣文字漸變
外文關鍵詞: Bitmap, Morphing
相關次數: 點閱:1下載:0
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 點陣圖(Bitmap)是一種簡單利用位元值(bit)來表示圖形的一種方法, 而每個位元值為0或1。點陣文字(Bitmap Font)也是利用點陣圖形的方式來呈現文字。而我們更是容易在電腦或是其他電子設備中看見點陣文字的出現。一般而言,點陣圖的優點在於不是一種壓縮過的圖形,所以更好的被拿來應用在各種處理上。漸變式演算法是一種連續性的變形過程。被廣泛的被使用在動畫或是電影的變形效果中,使某一件物體變形成另一種物體,或是由人變成另一個人。而最常見的漸變式算法即是用內插法來呈現,然而使用內插法得到的結果往往產生斷裂或是不連續性破壞了整個圖形的結構。因此我們想去設計一個算法在圖形的漸變過程中可以盡量保持連接與維持相似的結構不被破壞。我們在此提出了一種在各種電子產品、網頁製作、或是電子書集中更好的呈現方式。而在本篇的論文當中,我們專注於雙色的點陣圖(黑與白),我們得到不錯且平滑的執行結果。此外,這個演算法也可以是用在小尺寸的顯示裝備或是移動裝置中。

    在本篇論文裡,我們應用在希臘文字、英文文字、中國文字還有一些圖形中,例如插圖或是多邊形。


    A bitmap can represent a image by using bits, and the value which are zero or one. Bitmap fonts consist of a matrix of dots or pixels representing the image of each glyph in each face and size. The bitmap font is a common format for printing and displaying on computers, and it is widely used to display characters or pictures. Generally speaking, the advantage of bitmap format is that bitmap will not compose the data and with no distortion after applying any operations. Morphing is a transforming process changes one image or shape into another. The fundamental method to morph an image is mapping the points one by one, and interpolation the points to get the result. However, the drawback with one-by-one point-mapping method is that points can be mapped randomly, the corresponding character may be broken into pieces and then the architecture is destroyed. Thus we want to design an algorithm which morphs the bitmap font from one input data to another, such that creating an animation of bitmap data, and more details are kept than mapping points one by one. Here we present an alternate real-time method which displays characters on electronics products, web-page, computer games, and electronic books(e-books). We only use monotone bitmap font and we expect the morphing processes to run smoothly. In this way we can overcome the drawbacks of one by one mapping method. Moreover, it is appropriate to apply bitmap font to small-size monitors or mobile devices.

    In this thesis, we apply this method on English characters, Chinese characters, and some bitmap images, such as illustration and polygons.

    1 Introduction 1 1.1 Related Works 2 1.2 Contribution 4 1.3 Thesis Organization 5 2 Preliminaries 6 2.1 Binary Image 6 2.2 Boundary Traversal 7 2.3 Read Input Data 8 3 Algorithm Overview 9 4 Phase I: Segmentation 13 4.1 Feature Point Detection 13 4.1.1 Define the feature points 14 4.1.2 Modify Feature Point 15 4.1.3 Modify method for Polygon 16 4.2 Boundary Segmentation 17 4.2.1 Search for The Same Pattern in Concern Area 18 4.2.2 Search for The Similar Pattern in Concern Area 19 4.2.3 Search for The Similar Pattern on Boundary 20 5 Phase II: Connectedness Guarantee 21 5.1 Segment Connectedness 22 5.1.1 One segment Connectedness 22 5.1.2 Multi-segment Connectedness 22 5.2 Interior Point and Boundary Connectedness 27 5.2.1 Relative Mapping 28 5.2.2 Local Mapping 29 6 Phase III: Morphing process 31 6.1 Frame generating 31 6.2 Straight Edges Enforcement 32 6.3 Hole and Cave Filling 33 6.3.1 Holes Filling 34 6.3.2 Boundary Caving Filling 35 7 Implementation and Experimentation 37 7.1 Implementation 37 7.2 Data Set 38 7.3 Example of some results 39 7.4 Experimentation 61 7.4.1 Time measure 61 7.4.2 Frames measure 62 7.4.3 Moving Distance measure 63 7.4.4 most points increased and decreased measure 65 8 Conclusions and Discussions 67 8.1 Conclusions 68 8.2 Discussions 69 8.2.1 Moving behavior 69 8.2.2 Search similar pattern 70 8.2.3 Path Connectedness 70

    [1] A. Lubiw, M. Petrick, and M. Spriggs, Morphing orthogonal planar graph drawings, in proceedings of the 17th annual ACM-SIAM Symposium on Discrete Algorithm (SODA), pp. 222–230, 2006.
    [2] A. Namane and M.A. Sid-Ahmed, Character scaling by contour method, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 12, pp. 600–606, 1990.
    [3] B.B. Chaudhuri and U. Garain, Automatic detection of italic, bold and all-capital words in document images, in proceedings of Fourteenth International Conference on Pattern Recognition, vol. 1, pp. 610–612, 1998.
    [4] C.B. Browne, P.Q. Scott, S. R. Bruce, G. Anthony, and G. A. Hill, Animated font characters, United States Patent, Patent No. US 6504545 B1, 2003.
    [5] C.B. Owen and F. Makedon, High quality alias free image rotation, Conference Record of the Thirtieth Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 115–119, 1996.
    [6] C.F.R. Weiman, Continuous anti-aliased rotation and zoom of raster images, in proceedings of the 7th annual conference on ACM-SIGGRAPH Computer graphics and interactive techniques, vol. 14, pp.286–293, 1980.
    [7] C.Y. Suen, M. Berthod, and S. Mori, Automatic recognition of handprinted characters —The state of the art, in proceedings of the IEEE, vol. 68, pp. 469–487, 1980.
    [8] G. Wolberg, Image morphing: a survey, The Visual Computer, vol. 14, pp. 360–372, 1998.
    [9] H.-J. Lee and J. Huang, Performance improvement techniques for Chinese character recognition, In proceedings of the Eighth Int’l Conference on Document Analysis and Recognition, vol. 2, pp. 710–714, 2005.
    [10] H.-S. Hou and H. Andrews, Cubic splines for image interpolation and digital filtering, IEEE Transactions on Speech, Acoustics, and Signal Processing, vol. 26, pp. 508–517, 1978.
    [11] J. André and I. Vatton, Contextual typesetting of mathematical symbols taking care of optical scaling, Institut National de Recherche en Informatique et en Automatique (INRIA), inria-00074701, version 1, 1993.
    [12] J.E. Wamock, The display of characters using gray level sample arrays, in proceeding of the 7th annual conference on ACM SIGGRAPH Computer Graphics and interactive techniques, pp. 302–307, 1980.
    [13] K. Mahata and A.G. Ramakrishnan, A novel scheme for image rotation for document processing, in proceedings of Int’l Conference on Image Processing, vol. 2, pp. 594–596, 2000.
    [14] L. Wang and T. Pavlidis, Direct gray-scale extraction of features for character recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, pp. 1053–1067, 1993.
    [15] M. Makova A new core-based morphing algorithm for polygons, in proceedings of CESCG, 2007.
    [16] M. Makova I. Kolingerova and J Parus, Core-based morphing algorithm for triangle meshes, in SIGRAD, pp. 43-50, 2008.
    [17] M. Makova J. Parus, I. Kolingerova and B. Benes An intuitive polygon morphing, The Visual Computer, vol. 26, pp. 205-215, 2010.
    [18] S. Kahan, T. Pavlidis, and H.S. Baird, Building a font and size independent character recognition system, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-9, pp. 274-288, 1987.
    [19] S. Schaefer, T. McPhail, and J. Warren, Image deformation using moving least squares, in ACM Transactions on Graphics (TOG), pp. 533-540, 2006.
    [20] S.-W. Lee, D.-J. Lee, and H.-S. Park, A new methodology for gray-scale character segmentation and recognition, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, pp. 1045-1050, 1996.
    [21] S.-Y. Lee, K.-Y. Chwa, J. Hahn, and S.-Y. Shin, Image morphing using deformation techniques, Journal of Visualization and Computer Animation, vol. 7, pp. 3-23, 1996.
    [22] T. Asano, S. Bitou, M. Motoki, and N. Usui, In-place algorithm for image rotation, in proceedings of 18th International Symposium (ISAAC), vol. 4853, pp. 704-715, 2007.
    [23] T. Beier and S. Neely, Feature-based image metamorphosis, in proceedings of the 19th annual conference on ACM-SIGGRAPH Computer graphics and interactive techniques, vol. 26, pp. 35-42, 1992.
    [24] Y. Li, S. Naoi, M. Cheriet, and C.Y. Suen, A segmentation method for touching italic characters, in porceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 2, pp. 594–597, 2004.
    [25] Y. Zhu, T. Tan, and Y. Wang, Font recognition based on global texture analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, pp. 1192–1200, 2001.

    無法下載圖示 全文公開日期 本全文未授權公開 (校內網路)
    全文公開日期 本全文未授權公開 (校外網路)

    QR CODE