A New Descriptor for Pattern Matching: Application to Identity Document Verification

Abstract

Identity document verification consists on checking its conformity to one or eventually a set of authentic documents. This verification is usually performed through visible patterns matching. In this paper, we propose a new efficient visual descriptor for pattern comparison. As most of existing descriptors incorporate either color or spatial information; the proposed descriptor, called Grid-3CD, includes both information. This descriptor is based on color connected components (CC) extracted from a quantified image. It consists of a set of 6-tuples computed on a grid of pixels sampled from the color-quantified image. The 6-tuple of a given pixel describes the density, the mass center, the bounding box and the color of the CC that contains this pixel. The efficiency of this descriptor for identity document verification is shown using two strategies of pattern comparison. The first one is unsupervised and based on a distance measure whereas the second is supervised and based on one-class Support Vector Machine (SVM). The experimentation of the new descriptor on four datasets of identity documents totaling 3250 documents shows an average accuracy of about 90%, outperforming state-of-the-art descriptors.