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Fingerprint matching using genetic algorithm and triangle descriptors

机译:使用遗传算法和三角形描述符进行指纹匹配

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Because of some complex distortions which occur in fingerprint, the fingerprint matching is still known as a difficult problem. In this paper we propose a fingerprint matching method based on genetic algorithm. Since in the low quality images, minutiae extraction error is high, so in this method we have used the local properties of minutiae. Also in this paper a new kind of triangle descriptors are proposed, which uses these descriptors properties, the approximated value of transfer parameters for alignment and similarity between two fingerprints can be attained. These descriptors have been used to generate the initial population and are applied to the genetic algorithm. The results show that using this method will increase the convergence speed of genetic algorithm significantly. Also appropriate values of transfer parameters are achieved directly using this method. The proposed method in this paper has been evaluated on FVC2002-DB1_B and comparing the aforementioned results with other papers results shows that our proposed method has a better performance in convergence speed.
机译:由于指纹中会出现一些复杂的失真,因此指纹匹配仍然是一个难题。本文提出了一种基于遗传算法的指纹匹配方法。由于在低质量的图像中,细节的提取误差很高,因此在这种方法中,我们使用了细节的局部属性。本文还提出了一种新型的三角形描述符,利用这些描述符的属性,可以获得两个指纹之间对齐和相似度的传递参数的近似值。这些描述符已用于生成初始种群,并已应用于遗传算法。结果表明,该方法将大大提高遗传算法的收敛速度。使用此方法也可以直接获得适当的传递参数值。在FVC2002-DB1_B上对本文提出的方法进行了评估,并将上述结果与其他论文进行比较,结果表明,本文提出的方法在收敛速度上具有更好的性能。

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