Finger Knuckle Print Based Authentication

نویسندگان

  • Ankur Jain
  • Richa Gupta
  • Madasu Hanmandlu
چکیده

-In this paper, we investigate a new approach for personal authentication using Finger-Knuckle-Print through a novel texture descriptor, Local Directional Pattern (LDP). The image is encoded with Local Directional Pattern, which enhances the information as each pixel is represented as a binary LDP code. The Finger-Knuckle-Print is divided into smaller areas and LDP histograms are extracted from each block, which are used to graphically represent the information. The experimental results demonstrate the effectiveness of LDP achieving 97.67% classification accuracy for finger knuckle print based authentication.

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تاریخ انتشار 2012