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.<>
A multi-resolution based approach for handwriting segmentation in gray-scale images
Proceedings of 1st International Conference on Image Processing ; 1 ; 159-163 vol.1
1994-01-01
414192 byte
Conference paper
Electronic Resource
English
A Multiresolution Based Approach for Handwriting Segmentation in Gray-scale Images
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