Deep discriminative representation for generic palmprint recognition

作者：

Highlights：

• Current palmprint recognition methods focused on particular scenarios or devices.

• Deep discriminative representation model proposed for generic palmprint recognition.

• Deep convolutional networks are learned to extract deep discriminative features.

• Experimented on popular contact-based (inc. multispectral) and contactless datasets.

• Proposed framework achieves state-of-the-art results in EER and ARR.

摘要

•Current palmprint recognition methods focused on particular scenarios or devices.•Deep discriminative representation model proposed for generic palmprint recognition.•Deep convolutional networks are learned to extract deep discriminative features.•Experimented on popular contact-based (inc. multispectral) and contactless datasets.•Proposed framework achieves state-of-the-art results in EER and ARR.

论文关键词：Generic palmprint recognition,Deep discriminative networks,Deep discriminative feature,DDF-CRC

论文评审过程：Received 30 November 2018, Revised 4 June 2019, Accepted 26 September 2019, Available online 27 September 2019, Version of Record 4 October 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.107071