Xinjian Chen

A new algorithm for distorted fingerprints matching based on normalized fuzzy similarity measure

Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel algorithm, normalized fuzzy similarity measure (NFSM), to deal with the nonlinear distortions. The proposed algorithm has two main steps. First, the template and input fingerprints were aligned. In this process, the local topological structure matching was introduced to improve the robustness of global alignment. Second, the method NFSM was introduced to compute the similarity between the template and input fingerprints. The proposed algorithm was evaluated on fingerprints databases of FVC2004. Experimental results confirm that NFSM is a reliable and effective algorithm for fingerprint matching with nonliner distortions. The algorithm gives considerably higher matching scores compared to conventional matching algorithms for the deformed fingerprints.

Segmentation of fingerprint images using linear classifier

An algorithm for the segmentation of fingerprints and a criterion for evaluating the block feature are presented. The segmentation uses three block features: the block clusters degree, the block mean information, and the block variance. An optimal linear classifier has been trained for the classification per block and the criteria of minimal number of misclassified samples are used. Morphology has been applied as postprocessing to reduce the number of classification errors. The algorithm is tested on FVC2002 database, only 2.45% of the blocks are misclassified, while the postprocessing further reduces this ratio. Experiments have shown that the proposed segmentation method performs very well in rejecting false fingerprint features from the noisy background.

An algorithm for distorted fingerprint matching based on local triangle feature set

Coping with nonlinear distortions in fingerprint matching is a challenging task. This paper proposes a novel method, a fuzzy feature match (FFM) based on a local triangle feature set to match the deformed fingerprints. The fingerprint is represented by the fuzzy feature set: the local triangle feature set. The similarity between the fuzzy feature set is used to characterize the similarity between fingerprints. A fuzzy similarity measure for two triangles is introduced and extended to construct a similarity vector including the triangle-level similarities for all triangles in two fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingerprints. The FFM method maps the similarity vector pair to a normalized value which quantifies the overall image to image similarity. The proposed algorithm has been evaluated with NIST 24 and FVC2004 fingerprint databases. Experimental results confirm that the proposed FFM based on the local triangle feature set is a reliable and effective algorithm for fingerprint matching with nonlinear distortions.

A fingerprint authentication system based on mobile phone

With the increasing volume of sensitive and private information stored in the mobile phone, the security issue of mobile phone becomes an important field to investigate. This paper proposes a fingerprint authentication system for mobile phone security application. A prototype of our system is developed from the platform of BIRD E868 mobile phone with external fingerprint capture module. It is composed of two parts. One is the front-end fingerprint capture sub-system, and the other is back-end fingerprint recognition system. A thermal sweep fingerprint sensor is used in the fingerprint capture sub-system to fit the limitations of size, cost, and power consumption. In the fingerprint recognition sub-system, an optimized algorithm is developed from the one participated in the FVC2004. The performance of the proposed system is evaluated on the database built by the thermal sweep fingerprint sensor.

Fake finger detection based on thin-plate spline distortion model

This paper introduces a novel method based on the elasticity analysis of the finger skin to discriminate fake fingers from real ones. We match the fingerprints before and after special distortion and gained their corresponding minutiae pairs as landmarks. The thin-plate spline (TPS) model is used to globally describe the finger distortion. For an input finger, we compute the bending energy vector by the TPS model and calculate the similarity of the bending energy vector to the bending energy fuzzy feature set. The similarity score is in the range [0, 1], indicating how much the current finger is similar to the real finger. The method realizes fake finger detection based on the normal steps of fingerprint processing without special hardware, so it is easily implemented and efficient. The experimental results on a database of real and fake fingers show that the performance of the method is available.

A secured mobile phone based on embedded fingerprint recognition systems

This paper presents a prototype design and implementation of secured mobile phones based on embedded fingerprint recognition systems. One is a front-end fingerprint capture sub-system and the other is a back-end fingerprint recognition system based on smart phones. The fingerprint capture sub-system is an external module which contains two parts: an ARM-Core processor LPC2106 and an Atmel Finger Sensor AT77C101B. The LPC2106 processor controls the AT77C101B sensor to capture the fingerprint image. In the fingerprint recognition system, a new fingerprint verification algorithm was implemented on internal hardwares. The performance of the proposed system, with 4.16% equal error rate (EER) was examined on Atmel fingerprints database. The average computation time on a 13 MHz CPU S1C33 (by Epson) is about 5.0 sec.

A Matching Algorithm Based on Local Topologic Structure

How to cope with non-linear distortions in the matching algorithm is a real challenge. In this paper, we proposed a novel fingerprint matching algorithm based on the local topologic structure and a novel method to compute the similarity between two fingerprints. The algorithm firstly aligns the template fingerprint and the input fingerprint. Then local topologic structure matching was introduced to improve the robustness of global alignment. Finally a novel method was introduced to compute the similarity between the template fingerprint and the input fingerprint. The proposed algorithm has been participated in Fingerprint verification competition (FVC2004). The performance was ranked 3rd position in open category in FVC2004.

Enhancement of low quality fingerprints based on anisotropic filtering

The enhancement of the low quality fingerprint is a difficult and challenge task. This paper proposes an efficient algorithm based on anisotropic filtering to enhance the low quality fingerprint. In our algorithm, an orientation filed estimation with feedback method was proposed to compute the accurate fingerprint orientation. The gradient-based approach was firstly used to compute the coarse orientation. Then the reliability of orientation was computed from the gradient image. If the reliability of the estimated orientation is less than pre-specified threshold, the orientation will be corrected by the mixed orientation model. And an anisotropic filtering was used to enhance the fingerprint, with the advantages of its efficient ridge enhancement and its robustness against noise in the fingerprint image. The proposed algorithm has been evaluated on the databases of Fingerprint verification competition (FVC2004). Experimental results confirm that the proposed algorithm is effective and robust for the enhancement of the low quality fingerprint.

A fingerprint authentication mobile phone based on sweep sensor

With the advancement of mobile technology, mobile phones can store significant amount of sensitive and private information. The security issue of mobile phones becomes an important field to investigate. This paper proposes a prototype of fingerprint authentication mobile phone based on sweep sensor MBF310. The prototype is composed of the front-end fingerprint capture sub-system and the back-end fingerprint recognition system. A sweep fingerprint sensor MBF310 is used to fit the request of the mobile phone in the field of the size, cost, and power consumption. The performance of the proposed prototype is evaluated on the database built by the sweep fingerprint sensor. The EER is 4.23%, and the average match time of the prototype is about 4.5 seconds.

A novel algorithm for distorted fingerprint matching based on fuzzy features match

Coping with non-linear distortions in fingerprint matching is a real challenging task. This paper proposed a novel method, fuzzy features match (FFM), to match the deformed fingerprints. The fingerprint was represented by the fuzzy features: local triangle features set. The similarity between fuzzy features is used to character the similarity between fingerprints. First, a fuzzy similarity measure for two triangles was introduced. Second, the result is extended to construct a similarity vector which includes the triangle-level similarities for all triangles in two fingerprints. Accordingly, a similarity vector pair is defined to illustrate the similarities between two fingerprints. Finally, the FFM measure maps a similarity vector pair to a scalar quantity, within the real interval [0, 1], which quantifies the overall image to image similarity. To validate the method, fingerprints of FVC2004 were evaluated with the proposed algorithm. Experimental results show that FFM is a reliable and effective algorithm for fingerprint matching with non-liner distortions.