A robust method for the recognition of palmprints

Palmprint recognition has received in the last 20 years a great deal of the research community's attention. In this paper a new palmprint matching approach based on corner feature point extraction is proposed. A 72-element fixed-length descriptor is used to capture distinctive information of each feature point neighborhood and to build a measure of similarity whilst their coordinates provide a measure of proximity between the points. Matching two images takes into account both similarity and proximity measures which converts into a cost minimization problem. Our experiments carried out on a database of 250 prints from the Poly U database have yielded very good results evidenced by an EER of 0.31%.