SCENE TEXT DETECTION WITH EXTREMAL REGION BASED CASCADED FILTERING
Li G(李根)1; Liu Jie(刘杰)1; Zhang Shuwu(张树武)1; Zheng Yang(郑阳)2
2016
Conference NameIEEE International Conference on Image Processing (ICIP)
Conference Date2016-09-25 ~ 2016-09-28
Conference Place美国, 菲尼克斯
Abstract
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.
KeywordText Detection Extremal Region Recursive Local Search Cascaded Filter
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14464
Collection数字内容技术与服务研究中心_新媒体服务与管理技术
Affiliation1.中国科学院自动化研究所
2.北京科技大学
Recommended Citation
GB/T 7714
Li G,Liu Jie,Zhang Shuwu,et al. SCENE TEXT DETECTION WITH EXTREMAL REGION BASED CASCADED FILTERING[C],2016.
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