scholarly journals Garber Filter Based Hybridized Algorithm For Feature Extraction From A Fuzzy Fingerprint Image

Proper extraction of fingerprint functions is important for matching the fingerprint algorithms. Different pieces of fingerprint information, such as rigid orientation and frequency should be taken into consideration for good results. The quality of a fingerprint image is often required to improve the function extraction process. In this article we introduce a Hybridized Garber Filter Algorithm (HGFA) for Fuzzy Fingerprint Image Feature Extraction for effective fingerprint recognition.This paper describes a fingerprint detection system consisting of image preprocessing, filtration, extraction and recognition matching.Preprocessing of images includes normalization based on median value and variation. In order to prepare the fingerprint image further processing, Gabor filters are extracted. The Poincaré index with a partitioning technique is used for the identification of a particular point. The extraction of the ridge line is shown and also the minute extraction with CN algorithm

2014 ◽  
Vol 519-520 ◽  
pp. 577-580
Author(s):  
Shuai Yuan ◽  
Guo Yun Zhang ◽  
Jian Hui Wu ◽  
Long Yuan Guo

Fingerprint image feature extraction is a critical step to fingerprint recognition system, which studies topological structure, mathematical model and extraction algorithm of fingerprint feature. This paper presents system design and realization of feature extraction algorithm for fingerprint image. On the basis of fingerprint skeleton image, feature points including ending points, bifurcation points and singular points are extracted at first. Then false feature points are detected and eliminated by the violent changes of ambient orientation field. True feature points are marked at last. Test result shows that the method presented has good accuracy, quick speed and strong robustness for realtime application.


2019 ◽  
Vol 16 (5) ◽  
pp. 781-785 ◽  
Author(s):  
Zhikun Chen ◽  
Junjun Jiang ◽  
Chong Zhou ◽  
Xinwei Jiang ◽  
Shaoyuan Fu ◽  
...  

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