Hierarchical partitioned least squares filter-bank for fingerprint enhancement
It is desirable to enhance the fingerprint image for achieving good fingerprint matching performance. In our earlier work, we have proposed a method for learning a set of partitioned least-squares filters from a given set of images and ground truth pairs. In this paper, we propose a refined approach to learn a class of hierarchical filter banks to extend our enhancement technique. The new technique is shown to obtain much better results particularly when the input image is not easily restored using our earlier technique. We evaluate the performance of our new approach to fingerprint enhancement filter design by assessing the effect of enhancement on performance of (i) fingerprint feature extraction and (ii) fingerprint matching.