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研究生： 陳建隆
Chien-Lung Chen
論文名稱： 應用改良式經驗模態分解法於消除文件影像中的不良光照現象
Application of An Improvement Empirical Mode Decomposition Method to Eliminate Unwanted Illumination Effects in Document Images
指導教授： 范國清
Kuo-Chin Fan
溫敏淦
Ming-Gang Wen
口試委員:
學位類別： 碩士
Master
系所名稱： 資訊電機學院 - 資訊工程學系
Department of Computer Science & Information Engineering
畢業學年度： 97
語文別： 中文
論文頁數： 89
中文關鍵詞： 不良光照 、光影移除 、背影透光 、不均勻光場 、經驗模態分解法
外文關鍵詞： improvement of EMD, EMD, uneven illumination, unwanted illumination
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    • 本篇論文針對傳統的經驗模態分解法 (Empirical Mode Decomposition, EMD) 提出一個改良的方法。不同於傳統的經驗模態分解法，本研究所提出的方法可節省大量的計算時間，將其應用在光影不均的影像強化時，幾乎可達到傳統的經驗模態分解法所能達到的效果。
    本研究並將此改良的方法應用在目前較少有相關文獻探討到的問題─背影透光的文件影像，這是其它光影校正的方法所無法解決的問題，例如，直方圖均化 (Histogram Equalization)。
    經實驗結果證明，本研究所提出的方法在文件影像受光的影響下，其所可能產生的問題，例如，曝光不足、曝光過度、不均勻光場、背影透光等問題均可有效的解決。

    In this thesis, an improved technique of Empirical Mode Decomposition(EMD) is proposed. Different from traditional empirical mode decomposition, the computational time of the improved technique can be greatly reduced to ensure real time processing. Moreover, the improved technique almost possesses the same result as the traditional empirical mode decomposition when applying the technique in removing uneven illumination for image enhancement with application in 3D OCR.
    We also employ the improved technique to remove background texts of document images caused by illumination, which was seldom discussed in previous literatures. It is still an unresolved problem by using other methods such as histogram equalization.
    As can be seen in the experimental results, the improved technique works well for document images in various illumination environments, such as overall darkness, overall brightness, uneven illumination, and background text document image. This work is a prerequisite to facilitate and ensure the success of later 3D OCR.

    中文摘要...............................................i Abstract...............................................ii 誌謝...................................................iii 目錄...................................................iv 圖目錄.................................................vi 表目錄.................................................viii 第一章 緒論............................................1 1.1 研究動機與目的.....................................1 1.2 相關研究...........................................2 1.3 系統架構...........................................4 1.4 論文架構...........................................6 第二章 相關技術討論....................................7 2.1 K-Means演算法......................................7 2.2 Min-max Distance演算法.............................13 2.3 自動二值化─Otsu演算法.............................15 2.4 直方圖均化(Histogram Equalization).................19 第三章 改良式經驗模態分解法(Improvement of EMD)........23 3.1 原理介紹...........................................23 3.2 演算法.............................................26 3.3 改良...............................................43 第四章 研究方法........................................47 4.1 前處理.............................................47 4.2 IEMD...............................................48 4.2.1 列校正遮罩.......................................48 4.2.2 行校正遮罩.......................................53 4.3 反射遮罩...........................................56 4.4 光影移除...........................................57 4.5 二值化.............................................58 第五章 實驗結果與討論..................................59 5.1 實驗結果...........................................59 5.2 討論...............................................72 第六章 結論與未來工作..................................74 6.1 結論...............................................74 6.2 未來工作...........................................75 參考文獻...............................................77

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