文字藝術是一種透過文字來表現影像內容的風格化藝術，比較常見的種類可分為ASCII Art、NPR Packing與拼貼，而上述所提到的文字藝術並不以文字本身的形狀結構去表現影像主體的輪廓線條，因此，本論文提出能夠自動辨識文字形狀拼貼影像輪廓的系統，使用者可輸入影像或單純輪廓影像，並藉由一些方法在影像前處理時，取得影像主要輪廓線條，再透過本系統提出的影像匹配模型找出能夠表現出影像輪廓的文字，並利用篩選與組合等機制，從中找出能夠呈現此影像的文字藝術。為了提升影像匹配速度，本系統採用GPU多執行緒的平行處理功能，並比較其單核心與多核心的效益，最後呈現系統自動產生的結果，以及本系統的限制與未來展望。

Word art is a kind of stylization art that represents the content of image through characters. More common types can be divided into ASCII Art, NPR Packing and Collage. But the aforementioned techniques do not represent the outline of the image contour by the shape structure of the characters themselves. Therefore, this paper proposes a system that can automatically recognize the shape of characters to collage image contours. A user can input an original image or simple contour images, and by some method in image pre-processing to obtain the main contour lines of the image. Then through the proposed image matching model to identify the outline of the character that can represent the image contour. Next we use selection and combination mechanisms to find the candidate character that can represent contour. In order to enhance the image matching speed, we use the GPU multi-thread parallel processing frameworks, and compare with those using single-core and multi-core ones. Finally, we show the results that are automatically generated by our system, as well as the limitations of the system and future prospects.

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