Abstract
This paper presents a new method for comparing and classifying lip print images. In the proposed method a lip print image is first binarized and then subjected to the Hough transform. As a result a collection of line segments approximating the lip print pattern is obtained. Each segment is described by its length, angle and midpoint coordinates. Lip prints are compared using the mean differences similarity measure. Presented studies tested the impact of different weights applied to segment’s characteristic features on lip print recognition results. After further improvements the presented method can be used in criminal identification systems.
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