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Proceedings Paper

An improved Gabor enhancement method for low-quality fingerprint images
Author(s): Hao Geng; Jicheng Li; Jinwei Zhou; Dong Chen
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Paper Abstract

The criminal’s fingerprints often refer to those fingerprints that are extracted from crime scene and have played an important role in police’ investigation and cracking the cases, but these fingerprints have features such as blur, incompleteness and low-contrast of ridges. Traditional fingerprint enhancement and identification methods have some limitations and the current automated fingerprint identification system (AFIS) hasn’t not been applied extensively in police’ investigation. Since the Gabor filter has drawbacks such as poor efficiency, low preciseness of the extracted ridge’s orientation parameters, the enhancements of low-contrast fingerprint images can’t achieve the desired effects. Therefore, an improved Gabor enhancement for low-quality fingerprint is proposed in this paper. Firstly, orientation image templates with different scales were used to distinguish the orientation images in the fingerprint area, and then orientation parameters of ridge were calculated. Secondly, mean frequencies of ridge were extracted based on local window of ridge’s orientation and mean frequency parameters of ridges were calculated. Thirdly, the size and orientation of Gabor filter were self-adjusted according to local ridge’s orientation and mean frequency. Finally, the poor-quality fingerprint images were enhanced. In the experiment, the improved Gabor filter has better performance for low-quality fingerprint images when compared with the traditional filtering methods.

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96751J (8 October 2015); doi: 10.1117/12.2199490
Show Author Affiliations
Hao Geng, Changsha Univ. (China)
Jicheng Li, National Univ. of Defense Technology (China)
Jinwei Zhou, National Univ. of Defense Technology (China)
Dong Chen, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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