Effective Fingerprint Quality Estimation for Diverse Capture Sensors

Sensors

Shan Juan Xie²  Sook Yoon³  Jinwook Shin¹ 

[1] Advanced Graduate Education Center of Jeonbuk for EIT-BK21, Chonbuk National University, 664-141 Ga Deokjin-Dong, Jeonju, Jeonbuk, 561-756, Korea;Department of Electronics and Information Engineering, Chonbuk National University, 664-141 Ga Deokjin-Dong, Jeonju, Jeonbuk, 561-756, Korea; E-Mails:;Department of Multimedia Engineering, Mokpo National University, 61 Dorim-ri, Cheonggye-myeon, Jeonnam, 534-729, Korea; E-Mail:

关键词: fingerprints;    sensor;    quality estimation;    SVM;    recognition;   

DOI  :  10.3390/s100907896

来源: mdpi

【 摘 要 】

Recognizing the quality of fingerprints in advance can be beneficial for improving the performance of fingerprint recognition systems. The representative features to assess the quality of fingerprint images from different types of capture sensors are known to vary. In this paper, an effective quality estimation system that can be adapted for different types of capture sensors is designed by modifying and combining a set of features including orientation certainty, local orientation quality and consistency. The proposed system extracts basic features, and generates next level features which are applicable for various types of capture sensors. The system then uses the Support Vector Machine (SVM) classifier to determine whether or not an image should be accepted as input to the recognition system. The experimental results show that the proposed method can perform better than previous methods in terms of accuracy. In the meanwhile, the proposed method has an ability to eliminate residue images from the optical and capacitive sensors, and the coarse images from thermal sensors.

【 授权许可】

CC BY   
© 2010 by the authors; licensee MDPI, Basel, Switzerland.