This paper studies the design of data fusion algorithm for asynchronous system with integer times sampling. Firstly, the multisensor asynchronous samplings is mapped to the basic axis, accordingly a sampling sequence of single sensor can be taken. Secondly, aiming at the sensor with the densest sampling points, the modified parallel filtering is given. Afterwards, the sequential filtering fusion method is introduced to deal with the case that there are multiple mapped measurements at some sampling point. Finally, a novel parallel filtering fusion algorithm for asynchronous system with integer times sampling is proposed. Besides, a judgment scheme to distinguish measurement number at every sampling point in the fusion period is also designed. One simple computer numerical value simulation is demonstrated to validate the effectiveness of the judgment scheme and the proposed asynchronous fusion algorithm.

This paper focuses on fingerprint minutia matching algorithm. A special minutia neighbor structure is proposed during the matching process in this algorithm. It can locate fingerprints using the singular from classification information. In addition, minutia structure can be used to save the time of matching minutia in a simple but effective way. Then, the matching of minutia is based on the changeable sized boundary box. At the same time, possible reference position is computed to make sure the algorithm more robust to nonlinear deformation from fingerprint images. Experimental results on Fingerprint verification competition FVC2004 databases show that this algorithm can speed up the matching of fingerprint database with a preferable performance.