An improved fingerprint image matching and multi-view fingerprint recognition algorithm

2018 ◽  
Vol 35 (3-4) ◽  
pp. 341-354
Author(s):  
Dewen SENG ◽  
Hanggi ZHANG ◽  
Xujian FANG ◽  
Xuefeng ZHANG ◽  
Jing CHEN
Keyword(s):  
Image Matching ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image

Multi-Template Processing of Fingerprint Recognition Algorithm

2014 ◽  
Vol 610 ◽  
pp. 332-338
Author(s):  
Lian Ying Zou ◽  
Ying Zhou ◽  
Xiang Dong ◽  
Yu Chen
Keyword(s):  
Image Processing ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Ridge Line ◽  
Black And White ◽  
White Point ◽  
Direction Filter ◽  
Fingerprint Feature ◽  
Line Texture

Using multi-template processing algorithm, the fingerprint features are accurately collected. Through normalization, make the black and white point contrast of the fingerprint image more obviously, strengthen the ridge line texture. Direction calculating algorithm is based on the grey value of the neighborhood pixels. It can be implemented simply and speedily. Through direction filter, noises can be removed, and the contrast of the fingerprint’s ridge lines and valley lines can be enhanced. After binary converting, all information of the fingerprint is stored with 0 and 1. The effect of thinning is to make the fingerprint image more distinct to extract the fingerprint feature point easily. These steps had been implemented on Altera DE2 board with HDL codes. The experimental results indicate that the multi-template algorithm of fingerprint image processing is correct and practicable.

Preprocessing and Feature Extraction, Coding, Matching Algorithm for Fingerprint Image

2013 ◽  
Vol 805-806 ◽  
pp. 1900-1906
Author(s):  
He Ping Jia
Keyword(s):  
Feature Extraction ◽  
Gabor Filter ◽  
Recognition Rate ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Development Platform ◽  
Traditional Algorithm ◽  
Fingerprint Image Enhancement ◽  
Global And Local

A set of fingerprint recognition algorithm was achieved mainly including Gamma controller normalization and equalizing, fingerprint image division, fingerprint image binarization and different direction Gabor filter for feature extraction; especially Fingerprint image enhancement and the textures based on Gabor filter, taking account of both global and local features of the fingerprints.using matlab 7.0 for development platform was verified,The experimental results showed the proposed algorithm can avoid all sorts of false characters more effectively and recognition rate is higher than traditional algorithm in the same conditions.

scholarly journals Pencocokan Citra Sidik Jari Menggunakan Korelasi Silang Ternormalisasi

2015 ◽  
Vol 11 (4) ◽  
pp. 144
Author(s):  
Bulkis Kanata
Keyword(s):  
Image Matching ◽  
Cross Correlation ◽  
Region Of Interest ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Image Capture ◽  
Matching Algorithm ◽  
Specific Part ◽  
Finger Pressure

<p>Fingerprint image matching is an important procedure in fingerprint recognition. Robust fingerprint image matching under a variety of different image capture conditions is difficult to achieve, because of changes in finger pressure, variation of the angle, etc. Fingerprint matching is very important for the development of fingerprint system recognition that is sensitive to finger pressure. This paper proposes a fingerprint matching algorithm that enables the so-called fingerprint template (extracted specific part (region of interest (ROI)) of a person’s fingerprints to be matched to the different fingerprint of the same person or different people taken on different time, angle and a different finger pressure using normalized cross-correlation (NCC). This algorithm was implemented in MATLAB. The results showed that the maximum NCC value for ROI of the source fingerprints and targets that was greater than 0.62 indicates a strong correlation or similarity.</p><p> </p>

Fingerprint Image Enhancement Algorithm Based on FDCT

2011 ◽  
Vol 255-260 ◽  
pp. 2047-2051 ◽  
Author(s):  
Chong Ben Tao ◽  
Guo Dong Liu
Keyword(s):  
Curvelet Transform ◽  
Input Image ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Threshold Function ◽  
Fingerprint Image ◽  
Fingerprint Enhancement ◽  
Fast Discrete Curvelet Transform ◽  
Fingerprint Image Enhancement ◽  
Enhancement Algorithm

Fingerprint enhancement is an essential preprocessing step and it is crucial for the efficiency of fingerprint recognition algorithm. We present an enhancement algorithm based on fast discrete curvelet transform (FDCT). First, implement positive transform on input image, namely decompose the image into coarse scales and fine scales coefficients. Then make use of a directional filter and a soft threshold function to enhance image and reduce noise respectively. Finally, implement inverse transform, and reconstruct the enhanced image. Experiments are carried out on FVC2004 databases. For bad quality fingerprints, the results indicate that the proposed algorithm has better enhancement and de-noising effect than traditional methods, and need less time.

scholarly journals Enhancing Fingerprint Image Recognition Algorithm Using Fractional Derivative Filters

2017 ◽  
Vol 7 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Hossein Baloochian ◽  
Hamid Reza Ghaffary ◽  
Saeed Balochian
Keyword(s):  
Fractional Derivative ◽  
Fractional Derivatives ◽  
Gabor Filter ◽  
Input Image ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Fingerprint Image ◽  
Direction Estimation ◽  
First Time

Abstract One of the most important steps in recognizing fingerprint is accurate feature extraction of the input image. To enhance the accuracy of fingerprint recognition, an algorithm using fractional derivatives is proposed in this paper. The proposed algorithm uses the definitions of fractional derivatives Riemann-Liouville (R-L) and Grunwald-Letnikov (G-L) in two sections of direction estimation and image enhancement for the first time. Based on it, new mask of fractional derivative Gabor filter is calculated. The proposed fractional derivative-based method enhances the image quality. This method enhances the structure of ridges and grooves of fingerprint, using fractional derivatives. The efficiency of the proposed method is studied in images of FVC2004 (DB1, DB2, DB3 and DB4) database and the results are evaluated using the criteria including entropy, average gradient, and edge intensity. Also, performance of the proposed method is compared with other technical methods such as Gabor filter. Based on the obtained results from the tests, the method is able to enhance the quality of fingerprint images significantly.

scholarly journals A Fingerprint Recognition Algorithm Combining Phase-Based Image Matching and Feature-Based Matching

2005 ◽  
pp. 316-325 ◽  
Author(s):  
Koichi Ito ◽  
Ayumi Morita ◽  
Takafumi Aoki ◽  
Hiroshi Nakajima ◽  
Koji Kobayashi ◽  
...  
Keyword(s):  
Image Matching ◽  
Recognition Algorithm ◽  
Fingerprint Recognition ◽  
Feature Based

Application of Fingerprint-Matching Algorithm in Smart Gun Using Touch-Less Fingerprint Recognition System

2020 ◽  
pp. 122-128
Author(s):  
Saifullah Khalid
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fingerprint Matching ◽  
Fingerprint Image ◽  
Matching Algorithm ◽  
Latent Fingerprint ◽  
Recognition Systems

Fingerprint recognition systems are widely used in the field of biometrics. Many existing fingerprint sensors acquire fingerprint images as the user's fingerprint is contacted on a solid flat sensor. Because of this contact, input images from the same finger can be quite different and there are latent fingerprint issues that can lead to forgery and hygienic problems. For these reasons, a touchless fingerprint recognition system has been investigated, in which a fingerprint image can be captured without contact. While this system can solve the problems which arise through contact of the user's finger, other challenges emerge.

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