Hash-based space partitioning approach to iris biometric data indexing

作者：

Highlights：

• Design of search threshold using feature deviation.

• Data storage architecture follows locality sensitive hashing.

• To speed up the process of searching and retrieval the data is stored in bins.

• For better accuracy, search is done in nearby bins based on quality of the query.

摘要

•Design of search threshold using feature deviation.•Data storage architecture follows locality sensitive hashing.•To speed up the process of searching and retrieval the data is stored in bins.•For better accuracy, search is done in nearby bins based on quality of the query.

论文关键词：Iris data,Biometric data indexing,Locality sensitive hashing,Hash-based space partitioning

论文评审过程：Received 6 February 2019, Revised 29 April 2019, Accepted 20 May 2019, Available online 21 May 2019, Version of Record 24 May 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.026