Vision-based single-stroke character recognition for wearable computing
buir.contributor.author | Çetin, A. Enis | |
buir.contributor.orcid | Çetin, A. Enis|0000-0002-3449-1958 | |
dc.citation.epage | 37 | en_US |
dc.citation.issueNumber | 3 | en_US |
dc.citation.spage | 33 | en_US |
dc.citation.volumeNumber | 16 | en_US |
dc.contributor.author | Özer, Ö. F. | en_US |
dc.contributor.author | Özün, O. | en_US |
dc.contributor.author | Tüzel, C. Ö. | en_US |
dc.contributor.author | Atalay, V. | en_US |
dc.contributor.author | Çetin, A. Enis | en_US |
dc.date.accessioned | 2016-02-08T10:35:28Z | |
dc.date.available | 2016-02-08T10:35:28Z | |
dc.date.issued | 2001 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.abstract | Particularly when compared to traditional tools such as a keyboard or mouse, wearable computing data entry tools offer increased mobility and flexibility. Such tools include touch screens, hand gesture and facial expression recognition, speech recognition, and key systems. We describe a new approach for recognizing characters drawn by hand gestures or by a pointer on a user's forearm captured by a digital camera. We draw each character as a single, isolated stroke using a Graffiti-like alphabet. Our algorithm enables effective and quick character recognition. The resulting character recognition system has potential for application in mobile communication and computing devices such as phones, laptop computers, handheld computers and personal data assistants. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T10:35:28Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2001 | en |
dc.identifier.doi | 10.1109/5254.940024 | en_US |
dc.identifier.eissn | 1941-1294 | |
dc.identifier.issn | 1541-1672 | |
dc.identifier.uri | http://hdl.handle.net/11693/24866 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/5254.940024 | en_US |
dc.source.title | IEEE Intelligent Systems | en_US |
dc.subject | Chain code | en_US |
dc.subject | Document analysis | en_US |
dc.subject | Finite state machines | en_US |
dc.subject | Head mounted devices | en_US |
dc.subject | Single stroke character recognition | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Cameras | en_US |
dc.subject | Character recognition | en_US |
dc.subject | Codes (symbols) | en_US |
dc.subject | Computer vision | en_US |
dc.subject | Data acquisition | en_US |
dc.subject | Finite automata | en_US |
dc.subject | Gesture recognition | en_US |
dc.subject | Helmet mounted displays | en_US |
dc.subject | Man machine systems | en_US |
dc.subject | Mobile telecommunication systems | en_US |
dc.subject | Personal digital assistants | en_US |
dc.subject | Wearable computers | en_US |
dc.title | Vision-based single-stroke character recognition for wearable computing | en_US |
dc.type | Article | en_US |
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