Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings |
| Herausgeber (Verlag) | Springer Verlag |
| Seiten | 1-13 |
| Seitenumfang | 13 |
| ISBN (Print) | 9783319231914 |
| Publikationsstatus | Veröffentlicht - 25 Aug. 2015 |
| Veranstaltung | 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015 - Valletta, Malta Dauer: 2 Sept. 2015 → 4 Sept. 2015 |
Publikationsreihe
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Band | 9256 |
| ISSN (Print) | 0302-9743 |
| ISSN (elektronisch) | 1611-3349 |
Abstract
Automatic handwriting recognition plays a crucial role because writing with a pen is the most common and natural input method for humans. Whereas many algorithms detect the writing after finishing the input, this paper presents a handwriting recognition system that processes the input data during writing and thus detects misspelled characters on the fly from their origin. The main idea of the recognition is to decompose the input data into defined structures. Each character can be composed out of the structures point, line, curve, and circle. While the user draws a character, the digitized points of the pen are processed successively, decomposed into structures, and classified with the help of samples. The intermediate classification allows a direct feedback to the user as soon as the input differs from a given character.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Theoretische Informatik
- Informatik (insg.)
- Allgemeine Computerwissenschaft
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Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings. Springer Verlag, 2015. S. 1-13 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9256).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - On-the-fly handwriting recognition using a high-level representation
AU - Reinders, Christoph
AU - Baumann, Florian
AU - Scheuermann, Björn
AU - Ehlers, Arne
AU - Mühlpforte, Nicole
AU - Effenberg, Alfred Oliver
AU - Rosenhahn, Bodo
N1 - Funding information: This work has been partially funded by the ERC within the starting grant Dynamic MinVIP.
PY - 2015/8/25
Y1 - 2015/8/25
N2 - Automatic handwriting recognition plays a crucial role because writing with a pen is the most common and natural input method for humans. Whereas many algorithms detect the writing after finishing the input, this paper presents a handwriting recognition system that processes the input data during writing and thus detects misspelled characters on the fly from their origin. The main idea of the recognition is to decompose the input data into defined structures. Each character can be composed out of the structures point, line, curve, and circle. While the user draws a character, the digitized points of the pen are processed successively, decomposed into structures, and classified with the help of samples. The intermediate classification allows a direct feedback to the user as soon as the input differs from a given character.
AB - Automatic handwriting recognition plays a crucial role because writing with a pen is the most common and natural input method for humans. Whereas many algorithms detect the writing after finishing the input, this paper presents a handwriting recognition system that processes the input data during writing and thus detects misspelled characters on the fly from their origin. The main idea of the recognition is to decompose the input data into defined structures. Each character can be composed out of the structures point, line, curve, and circle. While the user draws a character, the digitized points of the pen are processed successively, decomposed into structures, and classified with the help of samples. The intermediate classification allows a direct feedback to the user as soon as the input differs from a given character.
UR - http://www.scopus.com/inward/record.url?scp=84945972942&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23192-1_1
DO - 10.1007/978-3-319-23192-1_1
M3 - Conference contribution
AN - SCOPUS:84945972942
SN - 9783319231914
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1
EP - 13
BT - Computer Analysis of Images and Patterns - 16th International Conference, CAIP 2015, Proceedings
PB - Springer Verlag
T2 - 16th International Conference on Computer Analysis of Images and Patterns, CAIP 2015
Y2 - 2 September 2015 through 4 September 2015
ER -