An empirical study on iris recognition in a mobile phone

Dongik Kim, Yujin Jung, Kar Ann Toh, Byungjun Son, Jaihie Kim

Research output: Contribution to journalArticle

27 Citations (Scopus)

Abstract

The iris recognition on a mobile phone is different from the conventional iris recognition implemented on a dedicated device in that the computational power of a mobile phone and the space for placing NIR (near infrared) LED (light emitting diode) illuminators and iris camera are limited. This paper raises these issues in detail based on real implementation of an iris recognition system in a mobile phone and proposes some solutions to these issues. An experimental study was conducted to search for the relevant power and wavelength of NIR LED illuminators with their positioning on a phone for capturing a good quality iris image. Subsequently, in view of the disparity between the user's gazing point and the center of the iris camera which causes degradation of acquired iris images, an experiment was performed to locate the appropriate gazing point for good iris image capture. A fast eye detection algorithm was proposed for implementation under the mobile platform with low computational facility. The experiments were conducted on a currently released mobile phone and the results showed promising potential for adoption of iris recognition as a reliable authentication means. As a result, two 850 nm LEDs were selected for iris illumination at 1.1 cm away from the iris camera for the size of a 7 cm × 13.7 cm phone. In the performance, the recognition accuracy was 0.1% EER (equal error rate) and the eye detection rate with the speed of 17.64 ms on a mobile phone was 99.4%.

Original languageEnglish
Pages (from-to)328-339
Number of pages12
JournalExpert Systems with Applications
Volume54
DOIs
Publication statusPublished - 2016 Jul 15

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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