Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study

doi:10.1109/TIP.2015.2473105

CASIA OpenIR > 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

	Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study
	Shi, Cun-Zhao; Gao, Song; Liu, Meng-Tao; Qi, Cheng-Zuo; Wang, Chun-Heng; Xiao, Bai-Hua; Shi Cunzhao
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
	2015-12-01
卷号	24 期号:12 页码:4952-4964
文章类型	Article
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.
关键词	Character Recognition Stroke Detector Structure Part-based Model Tree-structure Spatiality Embedded Codeword
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TIP.2015.2473105
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研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000362008200010
引用统计	被引频次：28[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/10026
专题	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
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
第一作者单位	中国科学院自动化研究所
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.

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