字元擷取與影像修復應用於國畫

Text Extraction and Image Inpainting on Chinese Paintings

劉秋杏(Chiu-Hsing Liu)

指導教授 ： 顏淑惠

淡江大學/工學院/資訊工程學系碩士班/碩士(2005年)

https://doi.org/10.6846/TKU.2005.00230

摘要

本論文針對國畫中的字元做字元擷取的動作，並將取得的字元位置利用樣本比對方法，將影像修復回尚未有題字或是蓋印的原樣。國畫為歷史文件，為了讓國畫可以永久保存不受毀壞因此建立數位檔案，且可提供人們線上瀏覽使用；因有許多字體與印章大多是後人收藏時才題字或蓋印，所以我們除了取出國畫上的字體外，更進一步將有字體的部份修復回單純只有畫作的影像。
國畫中的字體並無一定位置，大多在整張影像的四周，而背景由山水到花鳥皆有，並無一定格式。我們提出以型態學的背景重建(morphological reconstruct- tion)取得與四邊相連的背景資訊，再將與原影像相減反白後，取得文字的影像。接著使用各種型態學運算(morphological operactions)及connected component analysis來找出字元區塊，最後使用樣本比對方法修補得到的字元區塊。我們所提出的方法，經過實驗大多可得到令人滿意的成果。

關鍵字

國畫 ； 字元擷取 ； 影像修復 ； 型態學運算 ； 連接的元件分析

並列摘要

More and more Chinese paintings are digitalized and browsed by people on the Internet. This paper proposes a two-folded scheme to extract calligraphy and seals from Chinese painting images and inpaint the original images such that images contain painting only.
To accomplish the extraction task, a morphological operation, reconstruction by erosion, is used to remove most content of a painting (i.e. background). Consequently, background positioned in the center and connected to borders of the image will be removed. As a result, calligraphy and seals become the principal object and making extraction task much simplified. To accomplish the inpainting task, an adaptive sampling selection method is used for automatically choosing a sample most close to the damaged pixel for inpainting. The proposed algorithm has been executed on a set of Chinese paintings and proved its efficacy.

並列關鍵字

Chinese Paintings ； Text Extraction ； Morphological Reconstruction ； Image Inpainting ； Connected Component Analysis

參考文獻

[1] Sittisak Rodtook, Yuttapong Rangsanseri, “Adaptive Thresholding of Document Images Based on Laplacian Sign,” International Conference on Information Technology : Coding and Computing, April 02-04, 2001, pp.501-505

[3] Keechul Jung, Kwang In Kim, Anil K. Jain, “Text information extraction in images and video : a survey,” Pattern Recognition Volume: 37, Issue: 5, May, 2004, pp.977-997.

[4] Wang E. K., Minya Chen, “A new robust algorithm for video text extraction,” Pattern Recognition Volume: 36, Issue: 6, June, 2003, pp.1397-1406

[5] Kongqiao Wang, Jari A. Kangas, “Character location in scene images from digital camera,” Pattern Recognition Volume: 36, Issue: 10, October, 2003 pp.2287-2299.

[6] Yassin M. Y. Hasan, Lina J. Karam, “Morphological Text Extraction from Images,” IEEE Transactions on Image Processing, Volume: 9, Issue: 11, November, 2000 pp.1978-1983.