Deep Contextual Stroke Pooling for Scene Character Recognition
Zhang, Zhong1,2; Wang, Hong1,2; Liu, Shuang1,2; Xiao, Baihua3
Source PublicationIEEE ACCESS
2018
Volume6Pages:16454-16463
SubtypeArticle
AbstractCharacters, as a kind of symbols carrying rich semantic information, are composed of strokes arranged in a certain structure and are of great significance in our daily life. In this paper, we are concerned with the problem of scene character recognition, and study the problem from the perspective of feature representation. We propose a novel pooling method termed deep contextual stroke pooling (DCSP) for scene character recognition. The proposed DCSP discovers the most prominent stroke information by using stroke detectors and captures the spatial context of discriminative strokes by learning contextual factor. Specifically, we first utilize the convolutional summing map in one convolutional layer to select discriminative strokes and use the convolutional activation features of discriminative strokes to train stroke detectors. Then, we propose the contextual factor to represent the co-occurrence probability of the stroke and its location. Finally, in the response regions, we incorporate the contextual factor into the detector scores and obtain the deep contextual confidence vectors of scene characters. Extensive experiments are conducted on three databases, i.e., ICDAR2003, Chars74k, and SVIIN, and the experimental results demonstrate that our method achieves higher accuracies than the state-of-the-art methods.
KeywordScene Character Recognition Deep Contextual Stroke Pooling Contextual Factor
WOS HeadingsScience & Technology ; Technology
DOI10.1109/ACCESS.2018.2817342
WOS KeywordTEXT RECOGNITION ; IMAGE ; REPRESENTATION ; GESTURES
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61501327 ; Natural Science Foundation of Tianjin(17JCZDJC30600 ; Open Projects Program of the National Laboratory of Pattern Recognition(201700001 ; China Scholarship Council(201708120039 ; 61711530240) ; 15JCQNJC01700) ; 201800002) ; 201708120040)
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000429991600001
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21998
Collection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
Affiliation1.Tianjin Normal Univ, Tianjin Key Lab Wireless Mobile Commun & Power Tr, Tianjin 300387, Peoples R China
2.Tianjin Normal Univ, Coll Elect & Commun Engn, Tianjin 300387, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Intelligent Control Co, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Zhang, Zhong,Wang, Hong,Liu, Shuang,et al. Deep Contextual Stroke Pooling for Scene Character Recognition[J]. IEEE ACCESS,2018,6:16454-16463.
APA Zhang, Zhong,Wang, Hong,Liu, Shuang,&Xiao, Baihua.(2018).Deep Contextual Stroke Pooling for Scene Character Recognition.IEEE ACCESS,6,16454-16463.
MLA Zhang, Zhong,et al."Deep Contextual Stroke Pooling for Scene Character Recognition".IEEE ACCESS 6(2018):16454-16463.
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