MRF Based Text Binarization in Complex Images using Stroke Feature
文献类型：会议论文
| 作者 | Wang Yanna ; Shi Cunzhao; Wang Chunheng; Xiao Baihua
|
| 出版日期 | 2015 |
| 会议日期 | 2015.8.23-2015.8.26 |
| 会议地点 | France |
| 关键词 | Binarization Text Image Stroke Sub-image Weight Mrf |
| 英文摘要 | 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. |
| 会议录 | ICDAR
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12089]  |
| 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 |
| 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 |
| 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]. 见:. France. 2015.8.23-2015.8.26. |
入库方式： OAI收割
来源：自动化研究所
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