A multi-resolution based approach for handwriting segmentation in gray-scale images

Author

Cheriet, M. ; Thibault, R. ; Sabourin, R.

Author_Institution

Lab. d´´Image et de Modelisation Tridimensionnelle, Ecole de Technol. Superieure, Montreal, Que., Canada

Volume

1

fYear

1994

fDate

13-16 Nov 1994

Firstpage

159

Abstract

We present a new method to segment visual handwritten data in gray-scale images. In handwriting recognition, visual shapes are very important in improving the system´s performance. We introduce a robust method for extracting visual shapes of handwritten data from a noisy background. We adopted a multi-resolution Marr-Hildreth (1980) based approach to correctly segment visual data in variable contrasted images. Encouraging results have been obtained on real data, from the CEDAR database

Keywords

edge detection; feature extraction; handwriting recognition; image resolution; image segmentation; CEDAR database; Marr-Hildreth based approach; edge detector; gray-scale images; handwriting recognition; handwriting segmentation; multi-resolution based approach; robust method; system performance; variable contrasted images; visual handwritten data segmentation; visual shapes extraction; Background noise; Data mining; Gray-scale; Handwriting recognition; Image databases; Image segmentation; Multi-stage noise shaping; Robustness; Shape; System performance;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference

Conference_Location

Austin, TX

Print_ISBN

0-8186-6952-7

Type

conf

DOI

10.1109/ICIP.1994.413295

Filename

413295