Fingerprint Matching Based on Local Relative Orientation Field

A fingerprint matching method based on local relative orientation field is proposed. It extracts local relative orientation field around each minutia for minutiae matching. Local orientation features are also used to sorting minutiae in order to speed up searching a minutia when pairing minutiae. The experimental result reveals that this method achieves improved recognition accuracy. Key words fingerprint matching - ridge-based minutiae matching - local relative orientation field - sorting minutiae CLC number TP 391 Foundation item: Supported by the National Natural Science Foundation of China (60373023)Biography: ZHU En (1976-), male, Ph. D candidate, research direction: pattern recognition, image processing and information security.

5G Ultra-Dense Network Fingerprint Positioning Method Based on Matrix Completion

The problem of high-precision indoor positioning in the 5G era has attracted more and more attention.A fingerprint location method based on matrix completion(MC-FPL)is proposed for 5G ultradense networks to overcome the high costs of traditional fingerprint database construction and matching algorithms.First,a partial fingerprint database constructed and the accelerated proximal gradient algorithm is used to fill the partial fingerprint database to construct a full fingerprint database.Second,a fingerprint database division method based on the strongest received signal strength indicator is proposed,which divides the original fingerprint database into several sub-fingerprint databases.Finally,a classification weighted K-nearest neighbor fingerprint matching algorithm is proposed.The estimated coordinates of the point to be located can be obtained by fingerprint matching in a sub-fingerprint database.The simulation results show that the MC-FPL algorithm can reduce the complexity of database construction and fingerprint matching and has higher positioning accuracy compared with the traditional fingerprint algorithm.

Efficient Fingerprint Matching Algorithm for Integrated Circuit Cards

Fingerprint matching is a crucial step in fingerprint identification. Recently, a variety of algorithms for this issue have been developed. Each of them is application situation specific and has its advantages and disadvantages. It is highly desired to develop an efficient fingerprint verification technology for Integrated Circuit (IC) Cards or chips. IC cards have some special characteristics, such as very small storage space and slow processing speed, which hinder the use of most fingerprint matching algorithms in such situations. In order to solve this problem, the paper presents an improved minutia-pattern (minutiae-based) matching algorithm by employing the orientation field of the fingerprint as a new feature. Our algorithm not only inherits the advantages of the general minutia-pattern matching algorithms, but also overcomes their. disadvantages. Experimental results show that the proposed algorithm can greatly improve the performance of fingerprint matching in both accuracy and efficiency, and it is very suitable for applications in IC cards.

Fingerprint Representation Methods Based on B-Spline Functions

The global characteristics of a fingerprint image such as the ridge shape and ridge topology are often ignored in most automatic fingerprint verification system. In this paper, a new representative method based on B-Spline curve is proposed to address this problem. The resultant B-Spline curves can represent the global characteristics completely and the curves are analyzable and precise. An algorithm is also proposed to extract the curves from the fingerprint image. In addition to preserve the most information of the fingerprint image, the knot-points number of the B-Spline curve is reduced to minimum in this algorithm. At the same time, the influence of the fingerprint image noise is discussed. In the end, an example is given to demonstrate the effectiveness of the representation method. Key words fingerprint matching - B-spline interpolation - knots detection - parameterization - boundary condition CLC number TP 391. 41 Foundation item: Supported by the National Natural Science Foundation of China (90200400) and Wuhan Technology Committee (991009185G)Biography: Ruan Ke (1979-), male, Master candidate, research direction: digital image processing.

Coordinate correction algorithm for WLAN indoor positioning

In the fingerprint matching-based wireless local area network(WLAN) indoor positioning system,Kalman filter(KF) is usually applied after fingerprint matching algorithms to make positioning results more accurate and consecutive.But this method,like most methods in WLAN indoor positioning field,fails to consider and make use of users' moving speed information.In order to make the positioning results more accurate through using the users' moving speed information,a coordinate correction algorithm(CCA) is proposed in this paper.It predicts a reasonable range for positioning coordinates by using the moving speed information.If the real positioning coordinates are not in the predicted range,it means that the positioning coordinates are not reasonable to a moving user in indoor environment,so the proposed CCA is used to correct this kind of positioning coordinates.The simulation results prove that the positioning results by the CCA are more accurate than those calculated by the KF and the CCA is effective to improve the positioning performance.

Simultaneous extraction of level 2 and level 3 characteristics from latent fingerprints imaged with quantum dots for improved fingerprint analysis

Fingerprints are unique and life-long to everyone, so they occupy very important statuses in forensic science. However, due to the limit of current imaging technologies and instruments, recognition and matching of fingerprints are mostly based on their level 2 structures（bifurcation, crossover, and etc.）.Moreover, in real-world cases, fingerprints collected in the field are often incomplete or damaged, which adds further difficulty in fingerprint analysis. Quantum dots（QDs） are superior fluorescent imaging agents for latent fingerprints, which can provide both level 2 and level 3（sweat pores） details. Here, we used red-emitting N-acetylcysteine-capped Cd Te QDs as imaging agent for staining of eccrine LFPs. The numbers of level 2 and level 3 features that can be mapped are significantly larger than those obtained by cyanoacrylate fuming, a standard technique being adopted at forensic scene. Therefore, the level 2 and level 3 characteristics from QD-staining were simultaneously extracted for improved fingerprint analysis.A preliminary fingerprint matching based modified Pore Matching algorithm was thus developed based on the integration of both level 2 and level 3 characteristics. Satisfactory results of fingerprint matching were obtained, demonstrating the advantage of the QD-staining for advanced fingerprint analysis.

UWB positioning enhancement using Markov chain in indoor NLOS environment

The accuracy of the positioning system in indoor environment is often affected by none-line-of-sight(NLOS) propagation. In order to improve the positioning accuracy in indoor NLOS environment, a method used ultra-wide-band(UWB) technology, which based on time of arrival(TOA) principle, combining Markov chain and fingerprint matching was proposed. First, the TOA algorithm is used to locate the target tag. Then the Markov chain is used to identify if blocking happened and revise the position result. And the fingerprint matching is used to further improve the position accuracy. Finally, an experiment system was built to test the accuracy of the proposed method and the traditional Kalman filter method. The experimental results show that, compared with the traditional Kalman filter method, the proposed method can improve the positioning accuracy in indoor NLOS environment.