Hand-Geometry Recognition Using Entropy-Based Discretization |
| |
Authors: | Kumar A Zhang D |
| |
Affiliation: | Dept. of Electr. Eng., Indian Inst. of Technol. Delhi, New Delhi; |
| |
Abstract: | The hand-geometry-based recognition systems proposed in the literature have not yet exploited user-specific dependencies in the feature-level representation. We investigate the possibilities to improve the performance of the existing hand-geometry systems using the discretization of extracted features. This paper proposes employing discretization of hand-geometry features, using entropy-based heuristics, to achieve the performance improvement. The performance improvement due to the unsupervised and supervised discretization schemes is compared on a variety of classifiers: k-NN, naive Bayes, SVM, and FFN. Our experimental results on the database of 100 users achieve significant improvement in the recognition accuracy and confirm the usefulness of discretization in hand-geometry-based systems |
| |
Keywords: | |
|
|