Optimal segmentation of handwritten Chinese signatures using wavelet transforms

Abstract

We propose a new segmenting method for handwritten Chi- nese signatures based on the wavelet transform for signature verifica- tion. There are some differences in identifying a handwritten signature and in recognizing a handwritten character because there are meaning- ful features hidden in writing habits when an individual is signing his or her signature. These features exhibit themselves in the pen-down, pen- up, and in the corner of a stroke. Therefore the segmentation for identi- fying 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 inflec- tion points by detecting the zero-crossing points of the wavelet trans- forms of the input signature. Experimental results show that this new segmenting method has better segmentation capability than other meth- ods that are usually used. © 1996 Society of Photo-Optical Instrumentation Engi- neers.