Propose retina identification system based on the combination of SURF detector and BRISK descriptor

  • Matheel E. Abdulmunem Department of Computer Science, University of Technology, Baghdad, Iraq
  • Zainab H. Fatoohi Department of Computer Science, University of Technology, Baghdad, Iraq
Keywords: Retina, Speeded Up Robust Feature, Binary Robust Invariant Scalable Key-Points

Abstract

     In this paper the design of hybrid retina matching algorithm that is used in identification systems is considered. Retina based recognition is apparent as the most secure method for identification of an identity utilized to differentiate persons.

     The characteristics of Speeded up Robust Feature (SURF) and Binary Robust Invariant Scalable Key-Points (BRISK) algorithm have been used in order to produce a fast matching algorithm than the classical ones, those characteristics are important for real-time applications which usually need quick processing of a growing quantity of data. The algorithm is divided into three stages: retinal image processing and segmentation, extracting the local features from the retinal images using SURF and BRISK descriptors and finally matching those features using KNN matcher. The algorithm was trained with structured analysis of retina (STARE) database giving accuracy that reach 100%.

Published
2018-05-28
How to Cite
Abdulmunem, M. E., & Fatoohi, Z. H. (2018). Propose retina identification system based on the combination of SURF detector and BRISK descriptor. Iraqi Journal of Science, 59(2B), 946-955. Retrieved from https://ijs.uobaghdad.edu.iq/index.php/eijs/article/view/338
Section
Computer Science

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