SCENE TEXT DETECTION WITH EXTREMAL REGION BASED CASCADED FILTERING
文献类型：会议论文
| 作者 | Li G(李根)1 ; Liu Jie(刘杰)1; Zhang Shuwu(张树武)1; Zheng Yang(郑阳)2
|
| 出版日期 | 2016 |
| 会议日期 | 2016-09-25 ~ 2016-09-28 |
| 会议地点 | 美国, 菲尼克斯 |
| 关键词 | Text Detection Extremal Region Recursive Local Search Cascaded Filter |
| 英文摘要 |
In this paper, we present a robust Extremal Region (ER) based
scene text detection system. To eliminate the vast non-text
components generated by ER operator, a three-stage cascaded
filter is proposed. In the first stage, a powerful character classifier
enhanced by recursive local search is introduced to separate
text components from noises. Then, an efficient heuristic
pruning method is designed to further clean overlapped duplicate
characters. Finally, after text line construction, a cascaded
text line classification model integrating word entropy
and sliding window based CNN is proposed to remove false
text lines. Experiments on benchmarks show that our method
achieves state-of-the-art performance. |
| 语种 | 英语 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/14464]  |
| 专题 | 数字内容技术与服务研究中心_新媒体服务与管理技术 |
| 作者单位 | 1.中国科学院自动化研究所 2.北京科技大学 |
| 推荐引用方式 GB/T 7714 | Li G,Liu Jie,Zhang Shuwu,et al. SCENE TEXT DETECTION WITH EXTREMAL REGION BASED CASCADED FILTERING[C]. 见:. 美国, 菲尼克斯. 2016-09-25 ~ 2016-09-28. |
入库方式： OAI收割
来源：自动化研究所
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