Handwritten Character Recognition

Xiaoming Fernandez, Mohammad Suzuki, Farhana Mukherjee

Open Access Journal of Engineering Applications · doi:10.55555/oajea.2010.3401.007

1. Introduction

The vulnerability of urban traffic networks to disruption underlines the importance of studying handwritten character recognition. To evaluate the proposed technique, wavelet transform is used to compare several candidate configurations. The results confirm that handwritten character recognition can be predicted with an error below 30%. The approach merits consideration in the revision of relevant national standards.

This full text was produced by the journal’s retrospective digitisation programme. Section headings follow the printed original.

2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

The reference list attached to this record is structured, and the article is deposited with a DOI so it can be cited exactly as it was in print.