Applied Sciences (Mar 2022)

Improving Image Quality Assessment Based on the Combination of the Power Spectrum of Fingerprint Images and Prewitt Filter

  • Ting-Wei Shen,
  • Ching-Chuan Li,
  • Wan-Fu Lin,
  • Yu-Hao Tseng,
  • Wen-Fang Wu,
  • Sean Wu,
  • Zong-Liang Tseng,
  • Mao-Hsiu Hsu

DOI
https://doi.org/10.3390/app12073320
Journal volume & issue
Vol. 12, no. 7
p. 3320

Abstract

Read online

The assessment of fingerprint image quality is critical for most fingerprint applications. It has an impact on the performance and compatibility of fingerprint recognition, authentication, and built-in cryptosystems. This paper developed an improved fingerprint image quality assessment derived from the image power spectrum approach and combined it with the Prewitt filter and an improved weighting method. The conventional image power spectrum approach and our proposed approach were implemented for accuracy and reliability tests using good, faulty, and blurred fingerprint images. The experimental results showed the proposed algorithm accurately identified the sharpness of fingerprint images and improved the average difference in FIQMs to 61% between three different levels of blurred fingerprints compared with that achieved by a conventional algorithm.

Keywords