近年來數位相機普及，使得人們隨時可以藉相機取得影像；過去文字影像只能以紙本形式透過掃描機取得，現在則可利用相機隨時隨地在幾秒內得到各種實物上的文字影像。然而當透過相機取得越接近生活化的影像，因為取像環境的變異多元，形成了如影像光場不均問題、影像非平面化問題等新的研究課題，尤其是在光學文字辨識的應用上，這些新的問題產生了許多不良的影響。 目前文字辨識技術已能對單一文字非常正確的進行辨識，反而是如何取得單一文字的切割問題，因為以相機取像後所造成的視角差異、及文字影像不再是單純的分佈在同一平面等問題，成為有待努力的課題。本研究的研究目標即專注於文件因取像視角及文字分佈在不同平面等所造成的文件透視失真的文件變形矯正，針對日常生活中最常取得的圓柱上文件、立方體上非共平面文件、及非垂直取像光軸的透視失真文件進行分類與矯正研究。 本研究提出一個有效分割不同表面的文件影像矯正方法，利用影像前處理、連通標記擷取影像資料、文字行擷取流水演算法、及文件表面類別判斷，設計出有效的文件矯正方法。本研究所提出的矯正方法，不需使用文件邊界或排版格式的資訊，即可對常見文件影像因所在表面非單一平面的失真現象有不錯的矯正效果。 Recently, digital cameras become a universal device due to its cost down. People can capture images at will in any time. In the past, text images can only be acquired by scanning documents using scanners. Currently, we can obtain the images of any kinds of objects by simply using cameras within second. Resulting from the influences of environments existing in our daily life while capturing the object images, some new research topics arise, such as the space with uneven light-illumination and scene with more than one plane. Those new problems will definitely affect the performance of OCR (optical character recognition) drastically. Instead of focusing on OCR study which can already correctly recognize a single character with very high recognition rate currently, we devoting ourselves on slicing and obtaining a character from the images captured under poor conditions. For instance, the difference in view angles and texts do not distribute on the same plane. In this thesis, the research focuses on rectifying the documents with perspective distortions caused by different view angles while capturing images and various planes that texts locate on the image. In our work, we specially focus on classifying and rectifying images resided on cylinders, cubes of non-coplanar, and those captured through non-vertical light axis lens. This study provides an effective way in splitting an image with different planes and rectifying the split regions. The effective method in rectifying documents is designed mainly by using image processing techniques, such as connected-component labeling for extracting image information, text line extraction water flow algorithm, and image plane analysis. The proposed method can rectify those common document images with perspective distortion caused by non-singular planes without needing the information of document border and typesetting. Experimental results verify the feasibility and validity of our proposed method.
