XFinger-Net: Pixel-Wise Segmentation Method for Partially Defective Fingerprint Based on Attention Gates and U-Net

Partially defective fingerprint image (PDFI) with poor performance poses challenges to the automated fingerprint identification system (AFIS). To improve the quality and the performance rate of PDFI, it is essential to use accurate segmentation. Currently, most fingerprint image segmentations use methods with ridge orientation, ridge frequency, coherence, variance, local gradient, etc. This paper proposes a method of XFinger-Net for segmenting PDFIs. Based on U-Net, XFinger-Net inherits its characteristics. The attention gate with fewer parameters is used to replace the cascaded network, which can suppress uncorrelated regions of PDFIs. Moreover, the XFinger-Net implements a pixel-level segmentation and takes non-blocking fingerprint images as an input to preserve the global characteristics of PDFIs. The XFinger-Net can achieve a very good segmentation effect as demonstrated in the self-made fingerprint segmentation test.

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Extraction of Direction Features in Fingerprint Image

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.518.316 ◽

2014 ◽

Vol 518 ◽

pp. 316-319 ◽

Cited By ~ 2

Author(s):

Liang Zhang

Keyword(s):

Extraction Method ◽

Fingerprint Identification ◽

Identification System ◽

Fingerprint Image ◽

System Point ◽

Direction Image

This paper mainly discusses on the extraction method of an important feature----direction image in automatic fingerprint identification system, Point and block direction are respectively calculated of fingerprint image after preprocessing. The results in the paper could provide the basis for studying matching characteristics of subsequent fingerprint. All works achieved are performed in the VC environment.

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The Image Process Technology in Fingerprint Identification

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.433-440.3247 ◽

2012 ◽

Vol 433-440 ◽

pp. 3247-3251

Author(s):

Hai Yan Chen ◽

Ling Hui

Keyword(s):

Social Life ◽

Fingerprint Identification ◽

Biometric Identification ◽

Identification System ◽

Image Process ◽

Process Technology ◽

Fingerprint Image ◽

Image Preprocessing

Fingerprint identification technology is one of the biometric identification technologies that match and recognize the collected fingerprint image to determine the identity of the person. Fingerprint identification technology compared to other biometric identifications is more unique, practical and workable. Therefore, the fingerprint identification as the most popular, most convenient and most reliable authentication method, it has been widely used in many aspects of social life. This paper introduced the whole structure of the fingerprint identification system and the function of every part in fingerprint identification system, mainly introduced the part of fingerprint image pre-processing and implemented one of the algorithms for fingerprint image preprocessing with MATLAB. The result of the experiment shows that the algorithm for fingerprint image preprocessing that used in the paper meets the fingerprint image preprocessing requirements and it provides a basis for fingerprint characteristics extracting and fingerprint characteristics matching.

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Improving of Fingerprint Segmentation Images Based on K-MEANS and DBSCAN Clustering

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v9i4.pp2425-2432 ◽

2019 ◽

Vol 9 (4) ◽

pp. 2425 ◽

Cited By ~ 4

Author(s):

El mehdi Cherrat ◽

Rachid Alaoui ◽

Hassane Bouzahir

Keyword(s):

Computing Time ◽

Recognition System ◽

Fingerprint Recognition ◽

Identification System ◽

Fingerprint Image ◽

Local Variance ◽

Dbscan Clustering ◽

Matching Process ◽

Fingerprint Segmentation

<span lang="EN-US">Nowadays, the fingerprint identification system is the most exploited sector of biometric. Fingerprint image segmentation is considered one of its first processing stage. Thus, this stage affects typically the feature extraction and matching process which leads to fingerprint recognition system with high accuracy. In this paper, three major steps are proposed. First, Soble and TopHat filtering method have been used to improve the quality of the fingerprint images. Then, for each local block in fingerprint image, an accurate separation of the foreground and background region is obtained by K-means clustering for combining 5-dimensional characteristics vector (variance, difference of mean, gradient coherence, ridge direction and energy spectrum). Additionally, in our approach, the local variance thresholding is used to reduce computing time for segmentation. Finally, we are combined to our system DBSCAN clustering which has been performed in order to overcome the drawbacks of K-means classification in fingerprint images segmentation. The proposed algorithm is tested on four different databases. Experimental results demonstrate that our approach is significantly efficacy against some recently published techniques in terms of separation between the ridge and non-ridge region.</span>

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Fingerprint Image Segmentation using Deep Features and SVM

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b2371.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 1633-1638

Keyword(s):

Learning Algorithm ◽

Classification Problem ◽

Input Image ◽

Svm Classifier ◽

Identification System ◽

Fingerprint Image ◽

Wide Range ◽

Fingerprint Segmentation ◽

Sparse Autoencoder ◽

The Given

The task of fingerprint segmentation is the most important step in an automated fingerprint identification system. It is essential to separate the fingerprint foreground with ridge and valley structure from the background, which usually contains unwanted data hindering an accurate feature extraction. In the proposed method, fingerprint segmentation is treated as a classification problem by classifying the given input image into foreground class or background class. Here, we have used an unsupervised learning algorithm by using Stacked Sparse Autoencoder (SSAE) to learn the deep features which can very well distinguish the background region from foreground one. Finally, these deep features are given to the SVM classifier. The experimental results prove that the proposed method meets the state-of-the-art results in a wide range of applications.

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The Design of Fingerprint Identification System Based on TMS320VC5402

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.542-543.1339 ◽

2012 ◽

Vol 542-543 ◽

pp. 1339-1342 ◽

Cited By ~ 1

Author(s):

Xin Hong Su ◽

Li Qiang Yin ◽

Ling Gao ◽

Zhi Xia Zhang

Keyword(s):

Software Design ◽

High Reliability ◽

Low Cost ◽

Design Flow ◽

Fingerprint Identification ◽

Identification System ◽

Fingerprint Image ◽

Broad Application ◽

Design Software ◽

Application Prospects

Due to the unique and lifelong invariance characteristics of the fingerprint, this paper presents a fast fingerprint identification system by FPS200 solid-state fingerprint sensors and TMS320VC5402 DSP chip.In the system, FPS200 completed fingerprint collection, DSP chip to complete the fingerprint image pre processing of data; combined with the characteristics of the two chips, given the system hardware design, software design flow. The results showed that: the system is well designed, low cost, real-time and high reliability, with important practical value and broad application prospects.

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Research on Fingerprint Image Segmentation under Complex Background

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.687-691.3612 ◽

2014 ◽

Vol 687-691 ◽

pp. 3612-3615

Author(s):

Hong Xia Wang ◽

Ning Liu

Keyword(s):

Personal Identification ◽

Local Processing ◽

Post Processing ◽

Segmentation Method ◽

Fingerprint Image ◽

Complex Background ◽

Fingerprint Segmentation ◽

Three Stages ◽

Global And Local ◽

Global And Local Processing

Fingerprints are widely used in biometric techniques for automatic personal identification. In this paper, a fingerprint segmentation method is proposed to overcome the bad impact imposed by the complex background of the fingerprint image. The proposed approach is based on combining global and local processing to achieve segmentation of fingerprint images. The approach is implemented in three stages: preprocessing, segmentation, and post-processing. The effectiveness of the proposed method can be confirmed through the experimental results.

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A Gradient Based Approach for Fingerprint Image Segmentation using Morphological Operators

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.16244 ◽

2018 ◽

Vol 7 (4) ◽

pp. 2453

Author(s):

Reji Joy ◽

Hemalatha S

Keyword(s):

Image Segmentation ◽

Individual Recognition ◽

Input Image ◽

Fingerprint Recognition ◽

Identification System ◽

Morphological Operations ◽

Fingerprint Image ◽

Segmentation Process ◽

Gradient Based ◽

Fingerprint Segmentation

The advancement of science and technology has made the reliable individual recognition and identification systems to become very popular. From the various biometric characteristics, fingerprint is one of the popular method because of its easiness and not much effort is required to acquire fingerprint. First step for an Automated Fingerprint Identification System (AFIS) is the segmentation of fingerprint from the acquired image. During fingerprint segmentation process the input image is decomposed into foreground and background areas. The foreground area contains information that are needed in the automatic fingerprint recognition systems. However, the background is a noisy region that contributes to the extraction of false features. So in an AFIS, fingerprint image segmentation plays an important role in carefully separating ridge like part (foreground) from noisy background. Gradient based method is commonly used for segmentation process. Since gradient estimation is erroneous in noisy images, the study proposes a combination of gradient mask and morphological operations to segment fingerprint foreground effectively. The results obtained prove that the new method is suited for fingerprint segmentation.

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Aplicación del NFIS (Nist Fingerprint Image Software) para la Extracción de Características de Huellas Dactilares

Acta Universitaria ◽

10.15174/au.2005.222 ◽

2005 ◽

Vol 15 (1) ◽

pp. 29-35

Author(s):

Gerardo E. Canedo Romero ◽

Ma. de Guadalupe García Hernández ◽

Heriberto Gutiérrez Martín ◽

Noé Mosqueda Valadez

Keyword(s):

Fingerprint Identification ◽

Identification System ◽

Federal Bureau ◽

Fingerprint Image ◽

Federal Bureau Of Investigation

Este artículo presenta una descripción acerca de las huellas dactilares y sus características, así como la extracción de puntos característicos de la misma por medio del programa NFIS desarrollado por el NIST (National Institute of Standards and Technology) en conjunción con el FBI (Federal Bureau of Investigation), descripción de algunas herramientas, así como un panorama general de un sistema AFAS (Automatic Fingerprint Authentification System) y de un sistema AFIS (Automatic Fingerprint Identification System).

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