Biometric identification system by lip shape

Biometrics systems based on lip shape recognition is an interesting topic scarcely developed in the scientific literature. This is perhaps due to research's generalized belief of its scarcely discriminative power. However, a careful study shows that e difference among the outline of people's lip is greater than the difference among the shape at different lip images of the same person. So, biometric identification by lip outline is possible. In this paper the lip outline is obtained from a face color picture: the color image is transformed to gray scale by Chang, Huang and Novak transformation and binarized with the Ridler and Calvar threshold. Considering the lip centroid as origin of coordinates, each pixel lip envelopes is parameterized with polar (ordered from -pi to +pi) and cartesian coordinates (ordered as heights and widths). To asses the identity multilabeled multiparameter hidden Markov model is used with the polar coordinates and a multilayer neural network is applied to Cartesian coordinates. With a database of 50 people an average classification hit ratio of 96.9% and an Equal Error Ratio (EER) of 0.015 are obtained.