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.