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An efficient approach to recognise fingerprints

机译:识别指纹的有效方法

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摘要

Fingerprint analysis is typically based on the position and pattern of detected singular points in the fingerprint images. These singular points (cores and deltas) represent the characteristics of local ridge patterns, determine the topological structure (i.e., fingerprint type) and largely influence the orientation field. A core-delta relation is used as a global constraint for the final selection of singular points. This paper proposed an approach for singular points detection and then recognizes fingerprints based on singular points position and their relative distances. Experimental results show that the approach is efficient and robust, giving better results than existing dominant approaches.
机译:指纹分析通常基于指纹图像中检测到的奇异点的位置和模式。这些奇异点(核心和三角形)代表局部山脊模式的特征,确定拓扑结构(即指纹类型)并在很大程度上影响方向场。核心-增量关系用作最终选择奇异点的全局约束。本文提出了一种奇异点检测方法,然后根据奇异点位置及其相对距离识别指纹。实验结果表明,该方法高效,鲁棒,比现有的主流方法具有更好的效果。

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