- 學位論文
考慮字間相連性之資料導向手寫字合成技術
Data-driven Handwriting Synthesis with Conjoined Manner
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摘要
一個人的英文筆跡一般都會在一定的範圍內變動，並且每個字母的 手寫模樣與相鄰的字母彼此間也通常都有相當複雜的關係，而這種關 係會使得手寫字以及手寫段落的自動生成非常具有挑戰性。在這篇論 文中，我們提出一個根據書寫者的筆跡合成手寫字的方法。合成演算 法包含兩個部分：第一，我們根據書寫者的筆跡樣本，對每一個字母 建立一個外觀模型。第二，我們根據同一筆跡樣本計算字母與字母間 的相連機率，決定相鄰的字母間彼此是否要相連。因此，我們提出一 個新的模型用來計算字母間的相連軌跡，並同時考慮了上述兩個部分 。並且，這個模型亦會依據蒐集到的筆跡樣本合成單字。此外，段落 的排版也會根據此筆跡樣本自動生成。這個方法所產生的結果可以成 功地合成與書寫者提供的樣本具有相似筆跡的段落。
並列摘要
A person's handwriting appears differently within a typical range of variations, and the shapes of handwriting characters also show complex interaction with their nearby neighbours. This makes automatic synthesis of handwriting characters and paragraphs very challenging. In this paper, we propose a method for synthesizing handwriting texts according to a writer's handwriting style. The synthesis algorithm is composed by two phases. First, we create the shape models for different characters based on one writer's data. Then, we compute the cursive probability to decide whether each pair of neighbouring characters are conjoined together or not. By jointly modelling the handwriting style and conjoined property through a novel trajectory optimization, final handwriting words can be synthesized from a set of collected samples. Furthermore, the paragraphs' layouts are also automatically generated and adjusted according to the writer's style obtained from the same dataset. We demonstrate that our method can successfully synthesize an entire paragraph that imitate a writer's handwriting using his/her collected handwriting samples.
參考文獻
[1] A. Baumberg and D. Hogg. An efficient method for contour tracking using active
[2] J. R. Bellegarda. A data-driven affective analysis framework toward naturally expressive speech synthesis. Audio, Speech, and Language Processing, IEEE Transactions on, 19(5):1113–1122, 2011.
[3] D. Beymer and T. Poggio. Image representations for visual learning. Science,
[4] M. J. Black, D. J. Fleet, and Y. Yacoob. Robustly estimating changes in image appearance. Computer Vision and Image Understanding, 78(1):8–31, 2000.
[5] W.-D. Chang and J. Shin. A statistical handwriting model for style-preserving
延伸閱讀
- 余顯強（2005）。機讀編目格式與延伸標示語言互轉之定義研究。圖書與資訊學刊，(53)，18-30。https://doi.org/10.6575/JoLIS.2005.53.02
- 羅永聖（2008）。結合多類型字典與條件隨機域之中文斷詞與詞性標記系統研究〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2008.01118
- 洪士揚（1992）。以屬性字串比對法做線上草寫連體字辨識〔碩士論文，元智大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0009-0112200611302791
- 何恭毅（2011）。Optical Non-Contact of Handwriting Recognition System〔碩士論文，國立中央大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0031-1903201314414924
- Li, Z., & Ma, H. (2019). A Design and Implementation of Handwritten Digit Recognition Based on DBN. IETI Transactions on Engineering Research and Practice, 3(1), 1-12. https://doi.org/10.6723/TERP.201908_3(1).0001