Sinhala Handwriting Recognition Mechanism Using Zone Based Feature Extraction

dc.contributor.authorDharmapala, KAKND
dc.contributor.authorWijesooriya, WPMV
dc.contributor.authorChandrasekara, CP
dc.contributor.authorRathnapriya, UKAU
dc.contributor.authorRanathunga, L
dc.date.accessioned2017-03-11T10:09:18Z
dc.date.available2017-03-11T10:09:18Z
dc.description.abstractIdentification of Sinhala characters is considerably more difficult than other wide-spoken languages because of the complex shapes and similarities that are present within characters. With the addition of modifiers to the core characters, the recognition becomes increasingly more difficult. Most of the present systems only address the identification task of core characters which has potentially less real life applicability. The proposed solution tries to identify characters with or without touching and non-touching modifiers which can be effectively used in multiple applications.en_US
dc.identifier.conferenceITRU RESEARCH SYMPOSIUMen_US
dc.identifier.departmentDepartment of Information Technologyen_US
dc.identifier.emailvpowerrc@gmail.comen_US
dc.identifier.emailnaleendhanushka@gmail.comen_US
dc.identifier.emailchinthakacccc@gmail.comen_US
dc.identifier.emailamdevex@gmail.comen_US
dc.identifier.emaillochandaka@uom.lken_US
dc.identifier.facultyITen_US
dc.identifier.pgnos10-15en_US
dc.identifier.placeUNIVERSITY OF MORATUWAen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/12501
dc.identifier.year2015en_US
dc.language.isoenen_US
dc.subjectSinhala, Handwriting Recognition, Preprocessing, Character Segmentation, Classification, Neural Networks, Image Processing.en_US
dc.titleSinhala Handwriting Recognition Mechanism Using Zone Based Feature Extractionen_US
dc.typeConference-Full-texten_US

Files

Collections