Fingerprint indexing for wrinkled fingertips immersed in liquids

Abstract Wrinkled fingerprint recognition has been a challenging problem because of changing the position of fingertip features. This change significantly degrades the fingerprint recognition accuracy. Contactless dry three-dimensional (3D) fingerprints have the advantages of reducing the position change of fingertip features presented in both contact-based and contactless dry 2D fingerprints. Unfortunately, in contrast to the contactless dry 3D fingerprints, the position of features in the contactless wrinkled 3D fingerprints will be changed. Furthermore, identifying a fingerprint in a voluminous database is another challenge. With an increasing the number of individuals and inserting their fingerprints into the enrollment database, the cost of identification will increase and can become critical. Fingerprint indexing is a prominent method to reduce the response time of a probe in a large-scale database. The indexing approaches powerfully boost the recognition efficiency of dry fingerprints, but the accuracy of wrinkled fingerprints cannot be guaranteed. Moreover, previous indexing approaches only focused on dry 2D fingerprints and did not consider 3D fingerprints and the problems of wrinkled fingerprints. This paper proposes a 3D fingerprint reconstruction technique based on multi-view contactless wrinkled fingerprint images. In the proposed system, we use two cameras to acquire the frontal image. A dual camera can get more details of an image and is useful to acquire wrinkled fingerprints. In this paper, we propose a rectification technique for wrinkled 2D and 3D fingerprints as well. This paper also proposes a wrinkled fingerprint indexing approach to overcome the problems of wrinkled fingerprints. Our proposal employs minutiae quadruplets, ellipse properties, and a k-means clustering to index and retrieve fingerprints. Finally, a voting technique based on minutiae quality is proposed. Experimental results validate our approach and demonstrate the effectiveness of proposed method. Some new outlooks on the topics of 3D fingerprint acquisition, rectification and 3D reconstruction of wrinkled fingerprints, and fingerprint indexing are revealed. The main impact of this work is that more researchers will be attracted in related areas for wrinkled fingerprint recognition. The main significance is that the diversity of expert systems should be well promoted in addressing reconstruction of 3D shape and rectification of deformed fingerprints.