Building Skeletal Graphs for Structural Feature Extraction on Handwriting Images

Authors:
Affiliations:
Venue:
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Year:
2001

Citing 0
Cited 5

On the Dependence of Handwritten Word Recognizers on Lexicons

IEEE Transactions on Pattern Analysis and Machine Intelligence
A Stochastic Model Combining Discrete Symbols and Continuous Attributes and Its Application to Handwriting Recognition

DAS '02 Proceedings of the 5th International Workshop on Document Analysis Systems V
A New Feature Ranking Method in a HMM-Based Handwriting Recognition System

ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A Fast CBIR System of Old Ornamental Letter

Graphics Recognition. Recent Advances and New Opportunities
Graphical knowledge management in graphics recognition systems

GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Abstract: This paper presents a new method of building skeletal graphs for handwriting images, aiming at extraction of high-level structural features such as loops, turns, ends, and junctions. Block adjacency graphs are used as the base representation and transformed at locations where deformation occurs to obtain satisfactory skeletal graphs. Then the identification and ordering of structural features are considered based on skeletal graphs.