Metaclasses and Zoning Mechanism Applied to Handwriting Recognition

dc.creatorFreitas,Cinthia
dc.creatorOliveira,Luiz
dc.creatorAires,Simone B. K.
dc.creatorBortolozzi,Flávio
dc.date2008
dc.date.accessioned2024-02-06T12:56:12Z
dc.date.available2024-02-06T12:56:12Z
dc.descriptionThe contribution of this paper is twofold. First we investigate the use of the confusion matrices in order to get some insight to better define perceptual zoning for character recognition. The features considered in this work are based on concavities/convexities deficiencies, which are obtained by labelling the background pixels of the input image. Four different perceptual zoning (symmetrical and non-symmetrical) are discussed. Experiments show that this mechanism of zoning could be considered as a reasonable alternative to exhaustive search algorithms. The second contribution is a methodology to define metaclasses for the problem of handwritten character recognition. The proposed approach is based on the disagreement among the characters and it uses Euclidean distance computed between the confusion matrices. Through comprehensive experiments we demonstrate that the use of metaclasses can improve the performance of the system.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-014-02-0211
dc.identifierhttps://lib.jucs.org/article/28939/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/9601
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 14(2): 211-223
dc.subjectcharacter recognition
dc.subjectzoning mechanism
dc.subjectfeature measurement
dc.subjectmetaclasses
dc.subjectconfusion matrix
dc.titleMetaclasses and Zoning Mechanism Applied to Handwriting Recognition
dc.typeResearch Article
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