A novel approach for structural feature extraction: contour vs. direction

Authors:
Brijesh Verma;Michael Blumenstein;Moumita Ghosh
Affiliations:
School of Information Technology, Central Queensland University, Bruce Highway, Qld 4702, Australia;School of Information Technology, Griffith University, Parklands Drive, Qld 4215, Australia;School of Information Technology & Mathematical Sciences, University of Bailarat, P.O. Box 663, Ballarat VIC 3353, Australia
Venue:
Pattern Recognition Letters
Year:
2004

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Abstract

The paper presents a novel approach for extracting structural features from segmented cursive handwriting. The proposed approach is based on the contour code and stroke direction. The contour code feature utilises the rate of change of slope along the contour profile in addition to other properties such as the ascender and descender count, start point and end point. The direction feature identifies individual line segments or strokes from the character's outer boundary or thinned representation and highlights each character's pertinent direction information. Each feature is investigated employing a benchmark database and the experimental results using the proposed contour code based structural feature are very promising. A comparative evaluation with the directional feature and existing transition feature is included.