Arabic Handwritten Alphanumeric Character Recognition using Fuzzy Attributed Turning Functions

dc.contributor.authorMahmoud, Sabri
dc.contributor.authorParvez, Mohammad Tanvir
dc.date.accessioned2011-01-12T16:20:26Z
dc.date.available2011-01-12T16:20:26Z
dc.date.issued2011-01-12
dc.description.abstractIn this paper, we present a novel method for recognition of unconstrained handwritten Arabic alphanumeric characters. The algorithm binarizes the character image, smoothes it and extracts its contour. A novel approach for polygonal approximation of handwritten character contours is applied. The directions and length features are extracted from the polygonal approximation. These features are used to build character models in the training phase. For the recognition purpose, we introduce Fuzzy Attributed Turning Functions (FATF) and define a dissimilarity measure based on FATF for comparing polygonal shapes. Experimental results demonstrate the effectiveness of our algorithm for recognition of handwritten Arabic characters. We have obtained around 98% accuracy for Arabic handwritten characters and more than 97% accuracy for handwritten Arabic numerals.en
dc.identifier.urihttp://hdl.handle.net/2003/27563
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-12648
dc.language.isoen
dc.relation.ispartofFirst International Workshop on Frontiers in Arabic Handwritng Recognition, 2010en
dc.subjectCharacter Recognitionen
dc.subjectPolygonal Approximationen
dc.subjectTurning Functionsen
dc.subject.ddc004
dc.titleArabic Handwritten Alphanumeric Character Recognition using Fuzzy Attributed Turning Functionsen
dc.typeText
dc.type.publicationtypeconferenceObject
dcterms.accessRightsopen access

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