|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
|Source Publication||IEEE TRANSACTIONS ON IMAGE PROCESSING
|Abstract||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.|
Spatiality Embedded Codeword
|WOS Headings||Science & Technology
|WOS Keyword||OBJECT RECOGNITION
; SCENE IMAGES
; ORIENTED GRADIENTS
|WOS Research Area||Computer Science
|WOS Subject||Computer Science, Artificial Intelligence
; Engineering, Electrical & Electronic
|Corresponding Author||Shi Cunzhao|
|Affiliation||Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China|
|First Author Affilication||Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
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.
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.
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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