| MRF Based Text Binarization in Complex Images using Stroke Feature | |
Wang Yanna ; Shi Cunzhao; Wang Chunheng; Xiao Baihua
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| 2015 | |
| 会议名称 | International Conference on Document Analysis and Recognition (ICDAR) |
| 会议录名称 | ICDAR |
| 会议日期 | 2015.8.23-2015.8.26 |
| 会议地点 | France |
| 摘要 | This paper presents a novel binarization technique for text images based on Markov Random Field (MRF) framework. We regard stroke as an obvious feature of text to produce clustering result, which will be optimized by MRF model combining color, texture, context features to get the final binarization. The main innovations of our method are: (1) the integrated image is split into sub-images on which we can automatically acquire seed pixels of foreground and background using stroke feature; and (2) diverse weights are attached to seed pixels according to their location information, then highly confident cluster centers of sub-image can be acquired by gathering weighted seeds. The experimental results show that our method is robust and accurate on both video and scene images. |
| 关键词 | Binarization Text Image Stroke Sub-image Weight Mrf |
| 文献类型 | 会议论文 |
| 条目标识符 | http://ir.ia.ac.cn/handle/173211/12089 |
| 专题 | 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 |
| 通讯作者 | Shi Cunzhao |
| 作者单位 | The State Key Laboratory of Management and Control for Complex Systems,Institute of Automation, Chinese Academy of Sciences |
| 第一作者单位 | 中国科学院自动化研究所 |
| 通讯作者单位 | 中国科学院自动化研究所 |
| 推荐引用方式 GB/T 7714 | Wang Yanna,Shi Cunzhao,Wang Chunheng,et al. MRF Based Text Binarization in Complex Images using Stroke Feature[C],2015. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| ICDAR2015MRF Based T（1434KB） | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 | ||
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