DocumentCode :
1742960
Title :
A new segmentation approach for handwritten digits
Author :
De Oliveira, Luiz E Soares ; Lethelier, Edouard ; Bortolozzi, Flávio ; Sabourin, Robert
Author_Institution :
Pontificia Univ. Catolica do Parana, Brazil
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
323
Abstract :
This article deals with a new segmentation approach applied to unconstrained handwritten digits. The novelty of the proposed algorithm is based on the combination of two types of structural features in order to provide the best segmentation path between connected entities. This method was developed to be applied in a segmentation-based recognition system. In this article, we first present the features used to generate our basic segmentation points. Then, we define our segmentation paths depending on the encountered configurations with only few heuristic rules. Finally, we evaluate the output of our segmenter using a neural network trained with isolated digits
Keywords :
handwritten character recognition; heuristic programming; image segmentation; neural nets; configurations; heuristic rules; image segmentation; neural network; segmentation-based recognition system; structural features; unconstrained handwritten digits; Character generation; Character recognition; Focusing; Handwriting recognition; Image resolution; Image segmentation; Neural networks; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.906078
Filename :
906078
Link To Document :
بازگشت