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Personal identification based on handwriting
Said, HES; Tan, TN; Baker, KD
AbstractMany techniques have been reported for handwriting-based writer identification. The majority of techniques assume that the written text is fixed (e.g., in signature verification). In this paper we attempt to eliminate this assumption by presenting a novel algorithm for automatic text-independent writer identification. Given that the handwriting of different people is often visually distinctive, we take a global approach based on texture analysis, where each writer's handwriting is regarded as a different texture. In principle, this allows us to apply any standard texture recognition algorithm for the task (e.g., the multi-channel Gabor filtering technique). Results of 96.0% accuracy on the classification of 1000 test documents from 40 writers are very promising. The method is shown to be robust to noise and contents. (C) 1999 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
KeywordPersonal Identification Writer Identification Texture Analysis Gabor Filters Handwriting Processing Document Image Processing
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000083703300012
Citation statistics
Cited Times:169[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Univ Reading, Dept Comp Sci, Reading RG6 6AY, Berks, England
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Said, HES,Tan, TN,Baker, KD. Personal identification based on handwriting[J]. PATTERN RECOGNITION,2000,33(1):149-160.
APA Said, HES,Tan, TN,&Baker, KD.(2000).Personal identification based on handwriting.PATTERN RECOGNITION,33(1),149-160.
MLA Said, HES,et al."Personal identification based on handwriting".PATTERN RECOGNITION 33.1(2000):149-160.
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