Share Email Print

Proceedings Paper

Slant correction for handwritten English documents
Author(s): Malayappan Shridhar; Fumitaka Kimura; Yimei Ding; John W. V. Miller
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Optical character recognition of machine-printed documents is an effective means for extracting textural material. While the level of effectiveness for handwritten documents is much poorer, progress is being made in more constrained applications such as personal checks and postal addresses. In these applications a series of steps is performed for recognition beginning with removal of skew and slant. Slant is a characteristic unique to the writer and varies from writer to writer in which characters are tilted some amount from vertical. The second attribute is the skew that arises from the inability of the writer to write on a horizontal line. Several methods have been proposed and discussed for average slant estimation and correction in the earlier papers. However, analysis of many handwritten documents reveals that slant is a local property and slant varies even within a word. The use of an average slant for the entire word often results in overestimation or underestimation of the local slant. This paper describes three methods for local slant estimation, namely the simple iterative method, high-speed iterative method, and the 8-directional chain code method. The experimental results show that the proposed methods can estimate and correct local slant more effectively than the average slant correction.

Paper Details

Date Published: 16 December 2004
PDF: 9 pages
Proc. SPIE 5606, Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II, (16 December 2004); doi: 10.1117/12.580524
Show Author Affiliations
Malayappan Shridhar, Univ. of Michigan/Dearborn (United States)
Fumitaka Kimura, Mie Univ. (Japan)
Yimei Ding, Mie Univ. (Japan)
John W. V. Miller, Univ. of Michigan/Dearborn (United States)

Published in SPIE Proceedings Vol. 5606:
Two- and Three-Dimensional Vision Systems for Inspection, Control, and Metrology II
Kevin G. Harding, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?