期刊論文

標題 A Binarization Method with Learning-Built Rules for Document Images Produced by Cameras
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 英文(美國)
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 英國
公開徵稿
出版型式 紙本