A biometric scheme based on the silhouettes and/or textures of the hands is developed. The crucial part of the algorithm is the accurate registration of the deformable shape of the hands since subjects are not constrained in pose or posture during acquisition. A host of shape and texture features are comparatively evaluated, such as Independent component features (ICA features), Principal Component Analysis (PCA features), Angular Radial Transform (ART features) and the distance transform (DT) based features. Even with a limited number of training data it is shown that this biometric
scheme can perform reliably for populations up to several hundreds.