CRF based text detection for natural scene images using convolutional
文献类型：期刊论文
| 作者 | Wang YN(王燕娜)1,2 ; Shi,Cunzhao1; Baihua Xiao1; Chunheng Wang1; Chengzuo Qi1,2
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| 刊名 | Neurocomputing
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| 出版日期 | 2018 |
| 期号 | 295页码:46-58 |
| 关键词 | Scene Text Detection Mser Cnn Crf Context Information Shape-specific Classifiers |
| 英文摘要 | This paper presents a novel scene text detection method based on conditional random field (CRF) framework. We estimate the confidence of Maximally Stable Extremal Region (MSER) being text by leveraging convolutional neural network (CNN) to define the unary cost item. In addition, we establish the neighboring interactions for MSERs using four different features including color, shape, stroke and spatial features to define the pairwise cost item. Considering the special layout of texts appearing in natural scene images, we employ context information to recover missing text MSER candidates. Furthermore, text MSERs are grouped into candidate text lines which are verified with shape-specific classifiers by integrating gray and binary features. Experimental results on four public benchmark datasets show that the proposed method achieves the comparable performance. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/21036]  |
| 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 | 1.The State Key Laboratory of Management and Control for Complex Systems,Institute of Automation, Chinese Academy of Sciences 2.University of Chinese Academy of Sciences, Beijing, China |
| 推荐引用方式 GB/T 7714 | Wang YN,Shi,Cunzhao,Baihua Xiao,et al. CRF based text detection for natural scene images using convolutional[J]. Neurocomputing,2018(295):46-58. |
| APA | Wang YN,Shi,Cunzhao,Baihua Xiao,Chunheng Wang,&Chengzuo Qi.(2018).CRF based text detection for natural scene images using convolutional.Neurocomputing(295),46-58. |
| MLA | Wang YN,et al."CRF based text detection for natural scene images using convolutional".Neurocomputing .295(2018):46-58. |
入库方式： OAI收割
来源：自动化研究所
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