Statistics based segmentation and parameterization method for dynamic processing, identification, and verification of binary contour image

摘要

An improved method of segmentation and feature-based description for verification/authentication of contour images (e.g. handwritten signatures) is described, directed to a system which employs a set of parameters extracted from a dynamic description of a contour image template to perform segmentation of incoming contour images being verified/authenticated by the system. The preferred embodiment would consist of a central processing unit incorporating a high-performance computer, and of many autonomous verification units (e.g. ATM machines) equipped with inexpensive processing devices. In the central processing unit, a contour image template is segmented into strokes according to the segmentation parameters which are computed using selective properties of the mathematical transformation for said contour image template. For illustration purpose, a discrete cosine transform (DCT) is being used. The segmentation parameters, selective global parameters of the contour image, and selective features of the extracted strokes are memorized in a portable memory device. In a verification unit, an incoming contour image is normalized according to the global parameters retrieved from the portable memory device, then the incoming contour image is segmented according to the retrieved segmentation parameters, and finally the selective features are computed for the extracted strokes. The incoming contour image is accepted if the computed features and the corresponding features retrieved from the portable memory device satisfies a predetermined similarity criterion.