A Hand Contour Classification Using Ensemble of Natural Features: A Large Comparative Study

Abstract

Biometrics is a standalone scientific discipline which enjoys more and more attention of many researchers. The provision of the general security plays a key role in many modern branches. In the presented paper a person identification task is solved using the shape of a human hand, and also the hand contour classification algorithm based on an evolutionary estimator is also. The proposed methodology provides the comparison of the identified person with a set of model contours. The examination of the proposed method was performed with use of a database which contains 940 images of the scanned hands from 94 persons, including 10 images from every person. Totally 88360 combinations of the input images. The proposed evolutionary estimator uses an EPSDE algorithm, which is derived from a differential evolution algorithm which was proposed at the end of the 90’s. The model of the hand contour of every person is represented by only one image, which has movable finger contours in the classification process regarding the knuckle positions of the hand. Thanks to that, it is not necessary to use the pegs to hold the individual fingers in correct positions. The hand can be both placed on a support desk or can be freely hung in the air. All results obtained at classification time with use of the presented evolutionary estimator provide accuracy of approximately 98%.