Conference Paper

# Towards integrating level-3 Features with perspiration pattern for robust fingerprint recognition

Electr. & Comput. Eng Dept., Clarkson Univ., Potsdam, NY, USA

DOI: 10.1109/ICIP.2010.5654261 In proceeding of: Image Processing (ICIP), 2010 17th IEEE International Conference on Source: IEEE Xplore

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**ABSTRACT:**It has been shown that fingerprint scanners can be deceived very easily, using simple, inexpensive techniques. In this work, a countermeasure against such attacks is enhanced, that utilizes a wavelet based approach to detect liveness, integrated with the fingerprint matcher. Liveness is determined from perspiration changes along the fingerprint ridges, observed only in live people. The proposed algorithm was applied to a data set of approximately 58 live, 50 spoof and 28 cadaver fingerprint images captured at 0 and 2 s, from each of three different types of scanners, for normal conditions. The results demonstrate perfect separation of live and not live for the normal conditions. Without liveness module the commercially available verifinger matcher is shown to give equal error rate (EER) of 13.85% where false reject rate is calculated for genuine-live users and false accept rate is for genuine-not live, imposter-live and imposter-not live. The integrated system of fingerprint matcher and liveness module reduces EER to 0.03%. Results are also presented for moist and dry fingers simulated by glycerin and acetone, respectively. The system is further tested using gummy fingers and various deliberately simulated conditions including pressure change and adding moisture to the spoof to analyze the strength of the liveness algorithm.Pattern Recognition. 01/2009; - [Show abstract] [Hide abstract]

**ABSTRACT:**A multiscale Canny edge detection is equivalent to finding the local maxima of a wavelet transform. The authors study the properties of multiscale edges through the wavelet theory. For pattern recognition, one often needs to discriminate different types of edges. They show that the evolution of wavelet local maxima across scales characterize the local shape of irregular structures. Numerical descriptors of edge types are derived. The completeness of a multiscale edge representation is also studied. The authors describe an algorithm that reconstructs a close approximation of 1-D and 2-D signals from their multiscale edges. For images, the reconstruction errors are below visual sensitivity. As an application, a compact image coding algorithm that selects important edges and compresses the image data by factors over 30 has been implementedIEEE Transactions on Pattern Analysis and Machine Intelligence 08/1992; 14(7):710-732. · 4.80 Impact Factor - [Show abstract] [Hide abstract]

**ABSTRACT:**This paper presents a new approach for combining local and global recognition schemes for automatic fingerprint verification (AFV), by using matched local features as the reference axis for generating global features. In our specific implementation, minutia-based and shape-based techniques were combined. The first one matches local features (minutiae) by a point-pattern matching algorithm. The second one generates global features (shape signatures) by using the matched minutiae as its frame of reference. Shape signatures are then digitised to form a feature vector describing the fingerprint. Finally, a LVQ neural network was trained to match the fingerprints by using the difference of a pair of feature vectors. The experimental results show that the integrated system significantly outperforms the minutiae-based system in terms of classification accuracy and stability. This makes the new approach a promising solution for biometric applications.Pattern Recognition, 2002. Proceedings. 16th International Conference on; 02/2002

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