Biometric Authentication: A Machine Learning Approach

5. 1. Introduction

Neural networks have played a major role in many applications (e. g., see [171, 368]). In particular, they have demonstrated convincing performance in the detection and recognition of object classes. This is mainly due to their capability to cope with a variety of cues such as texture, intensity, edge, color and motion. In the context of personal identification, neural networks can facilitate detection or recognition of high-level features extracted from facial images or speakers' voices.

Supervised-learning network represent the mainstream of development in neural networks for biometric authentication. Some examples of well-known pioneering networks include the perceptron network [321], ADALINE/MADALINE [382], and various ...