Adaptive Fingerprint Image Enhancement with Emphasis on Preprocessing of Data

Summary, in English

This article proposes several improvements to an

adaptive fingerprint enhancement method that is based on

contextual filtering. The term adaptive implies that parameters

of the method are automatically adjusted based on the input

fingerprint image. Five processing blocks comprise the adaptive

fingerprint enhancement method, where four of these blocks are

updated in our proposed system. Hence, the proposed overall

system is novel. The four updated processing blocks are; preprocessing,

global analysis, local analysis and matched filtering.

In the pre-processing and local analysis blocks, a nonlinear

dynamic range adjustment method is used. In the global analysis

and matched filtering blocks, different forms of order statistical

filters are applied. These processing blocks yield an improved

and new adaptive fingerprint image processing method. The

performance of the updated processing blocks is presented in the

evaluation part of this paper. The algorithm is evaluated towards

the NIST developed NBIS software for fingerprint recognition on

FVC databases.

• Author: Josef Ström Bartunek; Mikael Nilsson; Benny Sällberg; Ingvar Claesson
• Department/s: Mathematics (Faculty of Engineering)
• Publishing year: 2013
• Language: English
• Pages: 644-656
• Publication/Series: IEEE Transactions on Image Processing
• Volume: 22
• Issue: 2
• Links: http://dx.doi.org/10.1109/TIP.2012.2220373
• Document type: Journal article
• Publisher: IEEE - Institute of Electrical and Electronics Engineers Inc.
• Topic: Mathematics
• Keywords: successive mean quantization transform; Fourier transform; image processing; directional filtering; spectral feature estimation
• Status: Published
• ISBN/ISSN/Other: ISSN: 1941-0042