Poor Quality Fingerprint Recognition Based on Wave Atom Transform

Fingerprint is considered the most practical biometrics due to some specific features which make them widely accepted. Reliable feature extraction from poor quality fingerprint images is still the most challenging problem in fingerprint recognition system. Extracting features from poor fingerprint images is not an easy task. Recently, Multi-resolution transforms techniques have been widely used as a feature extractor in the field of biometric recognition. In this paper we develop a complete and an efficient fingerprint recognition system that can deal with poor quality fingerprint images. Identification of poor quality fingerprint images needs reliable preprocessing stage, in which an image alignment, segmentation, and enhancement processes are performed. We improve a popular enhancement technique by replacing the segmentation algorithm with another new one. We use Waveatom transforms in extracting distinctive features from the enhanced fingerprint images. The selected features are matched throw K-Nearest neighbor classifier techniques. We test our methodology in 114 subjects selected from a very challenges database; CASIA; and we achieve a high recognition rate of about 99.5%

Improved fuzzy vault scheme for fingerprint verification

Fuzzy vault is a well-known technique to address the privacy concerns in biometric identification applications. We revisit the fuzzy vault scheme to address implementation, efficiency, and security issues encountered in its realization. We use the fingerprint data as a case study. We compare the performances of two different methods used in the implementation of fuzzy vault, namely brute force and Reed Solomon decoding. We show that the locations of fake (chaff) points in the vault leak information on the genuine points and propose a new chaff point placement technique that makes distinguishing genuine points impossible. We also propose a novel method for creation of chaff points that decreases the success rate of the brute force attack from 100% to less than 3.5%. While this paper lays out a complete guideline as to how the fuzzy vault is implemented in an efficient and secure way, it also points out that more research is needed to thwart the proposed attacks by presenting ideas for future research