Unified representation of online and offline hand drawn graphics using bezier curve approximation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, J. | - |
dc.contributor.author | Park, H.-H. | - |
dc.contributor.author | Kwon, Y.-B. | - |
dc.date.accessioned | 2021-09-16T08:40:43Z | - |
dc.date.available | 2021-09-16T08:40:43Z | - |
dc.date.issued | 2013 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.issn | 1611-3349 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/49321 | - |
dc.description.abstract | Integrating approaches in a unified system for the online and offline data type are seldom found, although the similar recognition alogirhtms are used for the two data stream. A practical solution which is able to represent online and offline hand drawn graphic messages simultaneously is presented. Freehand-sketched graphics captured by a digitizing tablet (online) or digital camera (offline) is approximated using the quadratic Bezier curve representation. A recursive architecture performing a piecewise curve approximation is proposed to represent pen strokes. As a primary unified tool for the online/offline symbol recognition system, a stroke ordering method which simulating online data of offline data is developed. The experimental results show good curve fitting and stroke generation ability of the proposed method, which can be applicable for practical real-time symbol recognition applications. © 2013 Springer-Verlag. | - |
dc.format.extent | 10 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.title | Unified representation of online and offline hand drawn graphics using bezier curve approximation | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/978-3-642-36824-0_14 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v.7423 LNCS, pp 139 - 148 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-84873968577 | - |
dc.citation.endPage | 148 | - |
dc.citation.startPage | 139 | - |
dc.citation.title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
dc.citation.volume | 7423 LNCS | - |
dc.type.docType | Conference Paper | - |
dc.publisher.location | 독일 | - |
dc.subject.keywordAuthor | Bezier Curve Approximation | - |
dc.subject.keywordAuthor | Online Offline Unification | - |
dc.subject.keywordAuthor | Unified Symbol Recognition | - |
dc.subject.keywordPlus | Bezier curve | - |
dc.subject.keywordPlus | Curve approximation | - |
dc.subject.keywordPlus | Data stream | - |
dc.subject.keywordPlus | Digitizing tablet | - |
dc.subject.keywordPlus | Hand-drawn | - |
dc.subject.keywordPlus | Offline | - |
dc.subject.keywordPlus | Offline data | - |
dc.subject.keywordPlus | Online data | - |
dc.subject.keywordPlus | Piece-wise | - |
dc.subject.keywordPlus | Practical solutions | - |
dc.subject.keywordPlus | Quadratic Bezier curve | - |
dc.subject.keywordPlus | Recursive architecture | - |
dc.subject.keywordPlus | Symbol recognition | - |
dc.subject.keywordPlus | Unified system | - |
dc.subject.keywordPlus | Curve fitting | - |
dc.subject.keywordPlus | Data integration | - |
dc.subject.keywordPlus | Interpolation | - |
dc.subject.keywordPlus | Pattern recognition | - |
dc.description.journalRegisteredClass | scopus | - |
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