Next Article in Journal
Periodic Cosmological Evolutions of Equation of State for Dark Energy 
Previous Article in Journal
On the Smoothed Minimum Error Entropy Criterion
Article Menu

Export Article

Open AccessArticle
Entropy 2012, 14(11), 2324-2350; doi:10.3390/e14112324

On Using Entropy for Enhancing Handwriting Preprocessing

1
Research Unit Human-Computer Interaction, Institute for Medical Informatics, Statistics and Documentation, Medical University Graz, Auenbruggerplatz 2/V, A-8036 Graz, Austria
2
Softnet Austria, Infeldgasse 16b, A-8010 Graz, Austria
*
Author to whom correspondence should be addressed.
Received: 21 July 2012 / Revised: 7 November 2012 / Accepted: 13 November 2012 / Published: 19 November 2012
View Full-Text   |   Download PDF [1746 KB, uploaded 24 February 2015]   |  

Abstract

Handwriting is an important modality for Human-Computer Interaction. For medical professionals, handwriting is (still) the preferred natural method of documentation. Handwriting recognition has long been a primary research area in Computer Science. With the tremendous ubiquity of smartphones, along with the renaissance of the stylus, handwriting recognition has become a new impetus. However, recognition rates are still not 100% perfect, and researchers still are constantly improving handwriting algorithms. In this paper we evaluate the performance of entropy based slant- and skew-correction, and compare the results to other methods. We selected 3700 words of 23 writers out of the Unipen-ICROW-03 benchmark set, which we annotated with their associated error angles by hand. Our results show that the entropy-based slant correction method outperforms a window based approach with an average precision of ±6.02° for the entropy-based method, compared with the ±7.85° for the alternative. On the other hand, the entropy-based skew correction yields a lower average precision of ±2:86°, compared with the average precision of ±2.13° for the alternative LSM based approach. View Full-Text
Keywords: entropy; handwriting recognition; point cloud data; preprocessing entropy; handwriting recognition; point cloud data; preprocessing
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Holzinger, A.; Stocker, C.; Peischl, B.; Simonic, K.-M. On Using Entropy for Enhancing Handwriting Preprocessing. Entropy 2012, 14, 2324-2350.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top