Noisy and incomplete fingerprint classification using local ridge distribution models

作者：

Highlights：

• A regional local model based fingerprint classification method is proposed.

• We make regional local models from the probability distributions of ridge directions.

• A classification accuracy based on the live scanned fingerprint databases is 97.4%.

• The classification performance is high for low quality and incomplete fingerprints.

摘要

•A regional local model based fingerprint classification method is proposed.•We make regional local models from the probability distributions of ridge directions.•A classification accuracy based on the live scanned fingerprint databases is 97.4%.•The classification performance is high for low quality and incomplete fingerprints.

论文关键词：Fingerprint classification,Ridge direction,Core block,Division of region,Conditional probability,Markov model

论文评审过程：Received 7 January 2014, Revised 23 June 2014, Accepted 30 July 2014, Available online 15 August 2014.

论文官网地址：https://doi.org/10.1016/j.patcog.2014.07.030