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  1. International Journal of Document Analysis and Recognition (IJDAR)
  2. International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
  3. International Journal of Document Analysis and Recognition (IJDAR) : Volume 2, Issue 1, July 1999
  4. Finding features used in the human reading of cursive handwriting
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International Journal of Document Analysis and Recognition (IJDAR) : Volume 20
International Journal of Document Analysis and Recognition (IJDAR) : Volume 19
International Journal of Document Analysis and Recognition (IJDAR) : Volume 18
International Journal of Document Analysis and Recognition (IJDAR) : Volume 17
International Journal of Document Analysis and Recognition (IJDAR) : Volume 16
International Journal of Document Analysis and Recognition (IJDAR) : Volume 15
International Journal of Document Analysis and Recognition (IJDAR) : Volume 14
International Journal of Document Analysis and Recognition (IJDAR) : Volume 13
International Journal of Document Analysis and Recognition (IJDAR) : Volume 12
International Journal of Document Analysis and Recognition (IJDAR) : Volume 11
International Journal of Document Analysis and Recognition (IJDAR) : Volume 10
International Journal of Document Analysis and Recognition (IJDAR) : Volume 9
International Journal of Document Analysis and Recognition (IJDAR) : Volume 8
International Journal of Document Analysis and Recognition (IJDAR) : Volume 7
International Journal of Document Analysis and Recognition (IJDAR) : Volume 6
International Journal of Document Analysis and Recognition (IJDAR) : Volume 5
International Journal of Document Analysis and Recognition (IJDAR) : Volume 4
International Journal of Document Analysis and Recognition (IJDAR) : Volume 3
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2, Issue 4, June 2000
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2, Issue 2-3, December 1999
International Journal of Document Analysis and Recognition (IJDAR) : Volume 2, Issue 1, July 1999
Frontiers in Handwriting Recognition
Handwriting recognition or reading? What is the situation at the dawn of the 3rd millenium?
Finding features used in the human reading of cursive handwriting
Global methods for stroke segmentation
Diacritical processing for unconstrained online handwriting recognition using a forward search
Recognition of handwritten numerals by Quantum Neural Network with fuzzy features
An architecture for handwritten text recognition systems
International Journal of Document Analysis and Recognition (IJDAR) : Volume 1

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Finding features used in the human reading of cursive handwriting

Content Provider Springer Nature Link
Author Schomaker, Lambert Segers, Eliane
Copyright Year 1999
Abstract This paper first summarizes a number of findings in the human reading of handwriting. A method is proposed to uncover more detailed information about geometrical features which human readers use in the reading of Western script. The results of an earlier experiment on the use of ascender/descender features were used for a second experiment aimed at more detailed features within words. A convenient experimental setup was developed, based on image enhancement by local mouse clicks under time pressure. The readers had to develop a cost-effective strategy to identify the letters in the word. Results revealed a left-to-right strategy in time, however, with extra attention to the initial, leftmost parts and the final, rightmost parts of words in a range of word lengths. The results confirm high hit rates on ascenders, descenders, crossings, and points of high curvature in the handwriting pattern.
Starting Page 13
Ending Page 18
Page Count 6
File Format PDF
ISSN 14332833
Journal International Journal of Document Analysis and Recognition (IJDAR)
Volume Number 2
Issue Number 1
Language English
Publisher Springer-Verlag
Publisher Date 1999-07-01
Publisher Place Berlin Heidelberg
Access Restriction One Nation One Subscription (ONOS)
Content Type Text
Resource Type Article
Subject Computer Science Applications Computer Vision and Pattern Recognition Software
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