Degraded document image binarization using structural symmetry of strokes
文献类型：期刊论文
| 作者 | Jia, Fuxi ; Shi, Cunzhao; He, Kun; Wang, Chunheng; Xiao, Baihua
|
| 刊名 | PATTERN RECOGNITION
 |
| 出版日期 | 2018-02-01 |
| 卷号 | 74期号:2018页码:225-240 |
| 关键词 | Document Image Binarization Structural Symmetry Of Strokes Local Threshold Stroke Width Estimation |
| DOI | 10.1016/j.patcog.2017.09.032 |
| 文献子类 | Article |
| 英文摘要 | This paper presents an effective approach for the local threshold binarization of degraded document images. We utilize the structural symmetric pixels (SSPs) to calculate the local threshold in neighborhood and the voting result of multiple thresholds will determine whether one pixel belongs to the foreground or not. The SSPs are defined as the pixels around strokes whose gradient magnitudes are large enough and orientations are symmetric opposite. The compensated gradient map is used to extract the SSP so as to weaken the influence of document degradations. To extract SSP candidates with large magnitudes and distinguish the faint characters and bleed-through background, we propose an adaptive global threshold selection algorithm. To further extract pixels with opposite orientations, an iterative stroke width estimation algorithm is applied to ensure the proper size of neighborhood used in orientation judgement. At last, we present a multiple threshold vote based framework to deal with some inaccurate detections of SSP. The experimental results on seven public document image binarization datasets show that our method is accurate and robust compared with many traditional and state-of-the-art document binarization approaches based on multiple evaluation measures. (C) 2017 Elsevier Ltd. All rights reserved. |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000417547800018 |
| 资助机构 | National Natural Science Foundation of China(61601462 ; 61531019 ; 71621002) |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19604]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_影像分析与机器视觉团队 |
| 作者单位 | Univ Chinese Acad Sci, Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Jia, Fuxi,Shi, Cunzhao,He, Kun,et al. Degraded document image binarization using structural symmetry of strokes[J]. PATTERN RECOGNITION,2018,74(2018):225-240. |
| APA | Jia, Fuxi,Shi, Cunzhao,He, Kun,Wang, Chunheng,&Xiao, Baihua.(2018).Degraded document image binarization using structural symmetry of strokes.PATTERN RECOGNITION,74(2018),225-240. |
| MLA | Jia, Fuxi,et al."Degraded document image binarization using structural symmetry of strokes".PATTERN RECOGNITION 74.2018(2018):225-240. |
入库方式： OAI收割
来源：自动化研究所
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