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Optical Engineering

Optimal segmentation of handwritten Chinese signatures using wavelet transforms
Author(s): Chi-Jain Wen; Hon-Fai Yau; Bor-Shenn Jeng
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Paper Abstract

We propose a new segmenting method for handwritten Chinese signatures based on the wavelet transform for signature verification. There are some differences in identifying a handwritten signature and in recognizing a handwritten character because there are meaningful features hidden in writing habits when an individual is signing his or her signature. These features exhibit themselves in the pen-down, penup, and in the corner of a stroke. Therefore the segmentation for identifying a signature and for recognizing a character should be different even though the same characters are involved. We propose to segment an input signature curve at the inflection points, and we locate the inflection points by detecting the zero-crossing points of the wavelet transforms of the input signature. Experimental results show that this new segmenting method has better segmentation capability than other methods that are usually used.

Paper Details

Date Published: 1 September 1996
PDF: 9 pages
Opt. Eng. 35(9) doi: 10.1117/1.600837
Published in: Optical Engineering Volume 35, Issue 9
Show Author Affiliations
Chi-Jain Wen, National Central Univ. (Taiwan)
Hon-Fai Yau, National Central Univ. (Taiwan)
Bor-Shenn Jeng, MOTC (Taiwan)

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