Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study
文献类型：期刊论文
| 作者 | Shi, Cun-Zhao ; Gao, Song; Liu, Meng-Tao; Qi, Cheng-Zuo; Wang, Chun-Heng; Xiao, Bai-Hua; Shi Cunzhao
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| 刊名 | IEEE TRANSACTIONS ON IMAGE PROCESSING
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| 出版日期 | 2015-12-01 |
| 卷号 | 24期号:12页码:4952-4964 |
| 关键词 | Character recognition stroke detector structure part-based model tree-structure spatiality embedded codeword |
| 英文摘要 | Characters, which are man-made symbols composed of strokes arranged in a certain structure, could provide semantic information and play an indispensable role in our daily life. In this paper, we try to make use of the intrinsic characteristics of characters and explore the stroke and structure-based methods for character recognition. First, we introduce two existing part-based models to recognize characters by detecting the elastic strokelike parts. In order to utilize strokes of various scales, we propose to learn the discriminative multi-scale stroke detector-based representation (DMSDR) for characters. However, the part-based models and DMSDR need to manually label the parts or key points for training. In order to learn the discriminative stroke detectors automatically, we further propose the discriminative spatiality embedded dictionary learning-based representation (DSEDR) for character recognition. We make a comparative study of the performance of the tree-structured model (TSM), mixtures-of-parts TSM, DMSDR, and DSEDR for character recognition on three challenging scene character recognition (SCR) data sets as well as two handwritten digits recognition data sets. A series of experiments is done on these data sets with various experimental setup. The experimental results demonstrate the suitability of stroke detector-based models for recognizing characters with deformations and distortions, especially in the case of limited training samples. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| 研究领域[WOS] | Computer Science ; Engineering |
| 关键词[WOS] | OBJECT RECOGNITION ; SCENE IMAGES ; ORIENTED GRADIENTS ; TEXT ; COOCCURRENCE ; SEGMENTATION ; EXTRACTION ; HISTOGRAM |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000362008200010 |
| 公开日期 | 2015-12-24 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/10026]  |
| 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 | Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Shi, Cun-Zhao,Gao, Song,Liu, Meng-Tao,et al. Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2015,24(12):4952-4964. |
| APA | Shi, Cun-Zhao.,Gao, Song.,Liu, Meng-Tao.,Qi, Cheng-Zuo.,Wang, Chun-Heng.,...&Shi Cunzhao.(2015).Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study.IEEE TRANSACTIONS ON IMAGE PROCESSING,24(12),4952-4964. |
| MLA | Shi, Cun-Zhao,et al."Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study".IEEE TRANSACTIONS ON IMAGE PROCESSING 24.12(2015):4952-4964. |
入库方式： OAI收割
来源：自动化研究所
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