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Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Automatic Segmentation of Unconstrained Handwritten Numeral Strings
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
J. Sadri, Concordia University
C. Y. Suen, Concordia University
T. D. Bui, Concordia University
A new method of segmenting unconstrained handwritten numeral strings is proposed. It is based on the extracting of foreground and background features. In order to find foreground features for the first time an algorithm based on skeleton tracing is introduced. The skeleton of each connected component is traversed in clockwise and anti-clockwise directions, and intersection points which are visited in each traversal, are mapped on the outer contour to form foreground feature points. In order to find background features, another new algorithm is proposed. Considering vertical projections of top and bottom profiles, two background skeletons are found. After processing these two background skeletons, background feature points are extracted. Background and foreground feature points are assigned together to construct candidate segmentation paths. Finally each segmentation path is evaluated based on the properties of its left and right connected components. Our method can provide a list of good segmentation hypotheses for segmentation-based recognition systems. The NIST SD19 Database (Handwritten numeral strings) is used for evaluating of the method, and experiments show a very promising result.
Index Terms:
Numeral String Segmentation, Numeral String Recognition, Foreground Features, Background Features, Skeleton Tracing
Citation:
J. Sadri, C. Y. Suen, T. D. Bui, "Automatic Segmentation of Unconstrained Handwritten Numeral Strings," iwfhr, pp.317-322, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
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