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    政大機構典藏 > 理學院 > 資訊科學系 > 學位論文 >  Item 140.119/83542
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/83542

    Title: 基於筆畫與結構分析之中文書法美感評估
    Aesthetic Evaluation of Chinese Calligraphy Based on Stroke and Structural Analysis
    Authors: 林育如
    Lin, Yuh Ru
    Contributors: 廖文宏
    Liao, Wen Hung
    Lin, Yuh Ru
    Keywords: 美感評估
    Aesthetic evaluation
    Kai style
    Stroke analysis
    Structural analysis
    Machine learning
    Date: 2016
    Issue Date: 2016-04-01 10:41:45 (UTC+8)
    Abstract: 中文書法經過了長久歷史的演變,已不單用來記錄事物,儼然成為了一種藝術。從古至今,有眾多書法大家和美學家撰寫書法專書,然而中文書法理論大多講述較抽象的技法,且在相關文獻鮮少之情況下難以具體將美感量化。本論文的目的為以電腦視覺角度解析中文書法筆畫與結構,找出影響書法美觀程度的視覺元素,並加以量化分析,透過機器學習機制,使電腦具有基本的書法鑑賞能力。有別於前人研究,我們提出6種描述整體楷書書法作品美感的特徵,包含排版工整度、字距掌握度、文字偏移程度、文字書寫大小穩定度、筆畫風格一致程度以及筆畫平滑程度。本研究蒐集書法比賽和素人作品共100張,每張皆經由一般母語為中文之受測者的評估,並且將得到的評分作為樣本的標籤,透過SVM辨識3個級別和5個級別的樣本,兩者皆有好的辨識效果。再者,我們將辨識結果轉換成美感分數,亦能真實呼應人工評分。透過我們的研究成果,期望能提供書法初學者在書法創作上的基礎參考標準。
    After a long history of evolution, Chinese calligraphy has transformed from a tool for writing to a unique form of art. Many publications regarding calligraphy writing techniques and appreciation have emerged along the way. Although the theory of Chinese calligraphy aesthetics is profound, it is difficult to define measures to quantify ‘beauty’ or ‘taste’. The objective of this research is to explore and extract relevant visual features for aesthetic evaluation of Chinese calligraphy using computer vision and machine learning techniques. Specifically, we propose six visual features to describe the quality of calligraphy work in Kai style, including layout, word separation, character offset, size regularity, style consistency and stroke uniformity. We then employ support vector machine (SVM) classifier to categorize the work into three or five levels of expertise. In both cases, good recognition results have been achieved. Furthermore, an aesthetic score can be obtained by converting the classification result with weighting factors. We hope that the evaluation result can assist beginners in identifying flaws in their writings and provide constructive suggestions to improve their skills in Chinese calligraphy.
    Reference: [1] 李賢輝,「視覺素養學習網」,http://vr.theatre.ntu.edu.tw/fineart/。
    [2] 房弘毅,「黃自元間架結構摘要九十二法」,中國書店,2005。
    [3] 蔡元培,「蔡元培文集(卷二).教育上」,錦繡出版社,台北市,民國84年。
    [4] 梁啟超,「飲冰室專集(五).作文教學法.書法指導」,中華書局,台北市,未標出版年。
    [5] 簡月娟,「書法美學研究方法論的省思」,興大中文學報第18期,民國95年1月,頁213-232。
    [6] Pak-keung Lai and Dit-yan Yeung, “Chinese glyph generation using character composition and beauty evaluation metrics”, Proceedings of the 1995 International Conference on Computer Processing of Oriental Languages, pp.92-99, 1995.
    [7] 張炘中,「漢字識別技術」,清華大學出版社,1992。
    [8] 房弘毅,「歐陽詢三十六法八訣」,中國書店,2005。
    [9] Dan Cires¸an and Jurgen Schmidhuber, “Multi-column deep neural networks for offline Handwritten Chinese character classification”, Technical Report, Aug 2013.
    [10] Yanwei Wang, Xin Li, Changsong Liu, Xiaoqing Ding and Youxin Chen, “An MQDF-CNN Hybrid Model for Offline Handwritten Chinese Character Recognition”, 14th International Conference on Frontiers in Handwriting Recognition (ICFHR), pp.246–249, 2014.
    [11] S.H. Xu, FCM Lau and Y. Pan, “A preliminary attempt at evaluating the beauty of Chinese calligraphy”, A Computational Approach to Digital Chinese Painting and Calligraphy, pp.253-284, 2009.
    [12] Rongju Sun, Zhouhui Lian, Yingmin Tang and Jianguo Xiao, “Aesthetic Visual Quality Evaluation of Chinese Handwritings”, Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015).
    [13] Jinjun Wang, Jianchao Yang, Kai Yu,Fengjun Lv, Thomas Huang, and Yihong Gong, “Locality-constrained linear coding for image classification”, Computer Vision and Pattern Recognition (CVPR), pp.3360–3367, 2010.
    [14] A Wilsona and A Chatterjee, “The assessment of preference for balance: Introducing a new test”, Empirical Studies of the Arts, vol. 23, pp.165-180, 2005.
    [15] Gershoni S and Hochstein S, “Measuring pictorial balance perception at first glance using Japanese calligraphy”, i-Perception, vol. 2 Issue 6, pp.508-527, 2011.
    [16] Boris Epshtein, Eyal Ofek, and Yonatan Wexler, “Detecting text in natural scenes with stroke width transform”, CVPR, pp.2963-2970, 2010.
    [17] 陳仕侗,「筆歌墨舞-書法欣賞」,
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0102753018
    Data Type: thesis
    Appears in Collections:[資訊科學系] 學位論文

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