Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/55359
Title: Improvement on gabor texture feature based biometric analysis using image blurring
Authors: Huang, D
Zhang, K
Zhang, D 
Keywords: Gabor filter
Gaussian filter
Image blurring
Iris recognition
Palmprint recognition
Issue Date: 2015
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Images without blurring are usually considered as high quality samples in biometric recognition. Image acquisition systems are carefully designed in order to capture clear images. However, experimental results show that the performance of Gabor texture feature based biometric recognition methods can be improved by image blurring. The experiments were conducted on the PolyU Palmprint Database using CompCode as well as on the CASIA Iris Database using Iris Code. The blurring method is to adopt a Gaussian filter to the images during pre-processing. Results indicate that there is an optimal range of each dataset and if all the images are blurred to this range, the performance of the whole dataset will reach optimal. A scheme is also proposed to find the optimal range and to blur an image to this range.
Description: 5th International Conference, IScIDE 2015, Suzhou, China, June 14-16, 2015
URI: http://hdl.handle.net/10397/55359
ISBN: 9783319239873
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-23989-7_43
Appears in Collections:Conference Paper

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