Finger-vein image matching based on adaptive curve transformation

作者：

Highlights：

• A set of spatial curve filters (SCFs) are designed using a variable curve model in curvature and orientation.

• A Gaussian weighted curve model is proposed to reduce filtering errors in fitting vein diameters.

• An efficient method is proposed for reliably estimating curve length fields (CLF). This can make SCFs adaptive to vein-width variations.

摘要

Highlights•A set of spatial curve filters (SCFs) are designed using a variable curve model in curvature and orientation.•A Gaussian weighted curve model is proposed to reduce filtering errors in fitting vein diameters.•An efficient method is proposed for reliably estimating curve length fields (CLF). This can make SCFs adaptive to vein-width variations.

论文关键词：Biometrics,Finger-vein recognition,Spatial curve filter,Vector field

论文评审过程：Received 2 August 2016, Revised 4 January 2017, Accepted 6 January 2017, Available online 7 January 2017, Version of Record 12 March 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.01.008