期刊論文
| 學年 | 98 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2010-04-01 |
| 作品名稱 | A Binarization Method with Learning-Built Rules for Document Images Produced by Cameras |
| 作品名稱（其他語言） | |
| 著者 | Chou, Chien-hsing; Lin, Wen-hsiung; Chang, Fu |
| 單位 | 淡江大學電機工程學系 |
| 出版者 | Kidlington: Pergamon |
| 著錄名稱、卷期、頁數 | Pattern Recognition 43(4), pp.1518-1530 |
| 摘要 | In this paper, we propose a novel binarization method for document images produced by cameras. Such images often have varying degrees of brightness and require more careful treatment than merely applying a statistical method to obtain a threshold value. To resolve the problem, the proposed method divides an image into several regions and decides how to binarize each region. The decision rules are derived from a learning process that takes training images as input. Tests on images produced under normal and inadequate illumination conditions show that our method yields better visual quality and better OCR performance than three global binarization methods and four locally adaptive binarization methods. |
| 關鍵字 | Document imagebinarization; Global threshold; Image processing;Local threshold;Multi-label problem;Non-uniform brightness;Support vectormachine |
| 語言 | en_US |
| ISSN | 0031-3203 |
| 期刊性質 | 國外 |
| 收錄於 | SCI EI |
| 產學合作 | |
| 通訊作者 | Chang, Fu |
| 審稿制度 | |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | 紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/55825 ) |