In these days, most fingerprint enrollment schemes for small mobile sensors ask the user cooperation to acquire wide finger coverage by requesting many input images. Nevertheless, it may still not be enough as some input images may cover the same part of the fingerprint. Therefore, we propose a novel enrollment scheme capturing all input images at one time by rubbing the finger on a sensor without touching-off during the whole enrollment process. Then, optimal image selection is followed for selecting best images among all input images to maximize the fingerprint coverage with less number of enrollment images. Experimental results showed that Equal Error Rate (EER) is about 30% improved compared to the conventional enrollment scheme.
|Title of host publication||International Conference on Electronics, Information and Communication, ICEIC 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||2|
|Publication status||Published - 2018 Apr 2|
|Event||17th International Conference on Electronics, Information and Communication, ICEIC 2018 - Honolulu, United States|
Duration: 2018 Jan 24 → 2018 Jan 27
|Name||International Conference on Electronics, Information and Communication, ICEIC 2018|
|Other||17th International Conference on Electronics, Information and Communication, ICEIC 2018|
|Period||18/1/24 → 18/1/27|
Bibliographical noteFunding Information:
This research was supported National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2016-006320).
© 2018 Institute of Electronics and Information Engineers.
All Science Journal Classification (ASJC) codes
- Information Systems
- Computer Networks and Communications
- Computer Science Applications
- Signal Processing
- Electrical and Electronic Engineering