The Experts below are selected from a list of 12270 Experts worldwide ranked by ideXlab platform
Xudong Jiang - One of the best experts on this subject based on the ideXlab platform.
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ICIP - Fingerprint Image quality analysis
2004 International Conference on Image Processing 2004. ICIP '04., 2004Co-Authors: P.n. Suganthan, Xudong JiangAbstract:Fingerprint Image quality analysis is crucial in eliminating poor Fingerprint Images, which will affect the performance of the automatic Fingerprint identification system. In this article, two types of new quality measures will be introduced: ridge and valley clarity and global orientation flow to calculate the overall Image quality score that can be used to quantitatively determine the quality of the Fingerprint Image. In order to evaluate the performance of the proposed algorithm, the quality measure is used to rank the performance of a Fingerprint recognition system and the ranking is compared with the quality measure rated manually. The result shows that the proposed scheme will return a score that ensures its reliability to indicate the quality of a given Fingerprint Image.
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Fingerprint Image quality analysis
2004 International Conference on Image Processing 2004. ICIP '04., 2004Co-Authors: P.n. Suganthan, Xudong JiangAbstract:This paper discusses methods in evaluating Fingerprint Image quality on a local level. Feature vectors covering directional strength, sinusoidal local ridge/valley pattern, ridge/valley uniformity and core occurrences are first extracted from Fingerprint Image subblocks. Each subblock is then assigned a quality level through pattern classification. Three different classifiers are employed to compare each of its different effectiveness. Positive results have been obtained based on our database.
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Fingerprint Image quality analysis
2004 International Conference on Image Processing 2004. ICIP '04., 2004Co-Authors: T.p. Chen, Xudong JiangAbstract:Fingerprint Image quality analysis is crucial in eliminating poor Fingerprint Images, which will affect the performance of the automatic Fingerprint identification system. In this article, two types of new quality measures will be introduced: ridge and valley clarity and global orientation flow to calculate the overall Image quality score that can be used to quantitatively determine the quality of the Fingerprint Image. In order to evaluate the performance of the proposed algorithm, the quality measure is used to rank the performance of a Fingerprint recognition system and the ranking is compared with the quality measure rated manually. The result shows that the proposed scheme will return a score that ensures its reliability to indicate the quality of a given Fingerprint Image.
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A study of Fingerprint Image filtering
Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205), 2001Co-Authors: Xudong JiangAbstract:Fingerprint Image enhancement is a crucial step in automatic Fingerprint recognition. A large number of approaches for filtering the Fingerprint Image have been suggested. Most of them perform oriented band pass filtering. However, such filters, for example, Gabor filters, may create spurious ridge structure information. This is harmful for the feature extraction and therefore is harmful for the automatic Fingerprint recognition. This paper examines the properties of applying the Gabor filter in the Fingerprint Image enhancement. It shows that the nonsinusoidal-shaped ridge structure, the ridge frequency estimation error, and the small filter size are the causes of creating spurious ridge structures. As a solution, we suggest an adaptive oriented low pass filter instead of the Gabor filter to avoid producing undesired harmful side effects for the automatic Fingerprint recognition.
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Fingerprint Image Processing for Automatic Verification
1999Co-Authors: Xudong JiangAbstract:The performance of an automatic Fingerprint verification approach relies heavily on the quality of the Fingerprint Image. Enhancement of the Fingerprint Image is then a crucial step in automatic Fingerprint verification. This paper discusses the Fingerprint Image processing methods for automatic verification and proposes an adaptive oriented low pass filter to enhance the Fingerprint Image quality. For automatic Fingerprint verification the Fingerprint Image processing is not aimed at improving the visual appearance of the Fingerprint Image but aimed at facilitating the subsequent processing. Therefore, the Fingerprint Image processing method is closely related to the method employed for the subsequent minutiae detection. The proposed approach takes efforts to increase the chances for success of the subsequent processes and at the same time avoid producing undesired side effects such as losing of the original ridge structure information or introducing additional spurious ridge structure information. Some sample results are given to illustrate the performance of the proposed approach.
Josef Bigun - One of the best experts on this subject based on the ideXlab platform.
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A Comparative Study of Fingerprint Image-Quality Estimation Methods
IEEE Transactions on Information Forensics and Security, 2007Co-Authors: Fernando Alonso-Fernandez, Hartwig Fronthaler, Klaus Kollreider, Joaquin Gonzalez-rodriguez, Javier Ortega-garcia, Julian Fierrez, Josef BigunAbstract:One of the open issues in Fingerprint verification is the lack of robustness against Image-quality degradation. Poor-quality Images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it is important for a Fingerprint recognition system to estimate the quality and validity of the captured Fingerprint Images. In this work, we review existing approaches for Fingerprint Image-quality estimation, including the rationale behind the published measures and visual examples showing their behavior under different quality conditions. We have also tested a selection of Fingerprint Image-quality estimation algorithms. For the experiments, we employ the BioSec multimodal baseline corpus, which includes 19 200 Fingerprint Images from 200 individuals acquired in two sessions with three different sensors. The behavior of the selected quality measures is compared, showing high correlation between them in most cases. The effect of low-quality samples in the verification performance is also studied for a widely available minutiae-based Fingerprint matching system.
Hong Wei Li - One of the best experts on this subject based on the ideXlab platform.
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Fingerprint Image segmentation based on a combined method
2012 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS) Proceedings, 2012Co-Authors: Hong Wei LiAbstract:Fingerprint Image segmentation is part of preprocessing in Fingerprint Image recognition system. It has a critical effect to the Fingerprint Image recognition system. A combined method segmentation method is proposed in this article. We use the orientation field information combined with statistical characteristics of gray. The Fingerprint Image realized the second segmentation with the method proposed in this paper. The experimental results show that the method used in this paper achieves a good effect.
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VECIMS - Fingerprint Image segmentation based on a combined method
2012 IEEE International Conference on Virtual Environments Human-Computer Interfaces and Measurement Systems (VECIMS) Proceedings, 2012Co-Authors: Hong Wei LiAbstract:Fingerprint Image segmentation is part of pre-processing in Fingerprint Image recognition system. It has a critical effect to the Fingerprint Image recognition system. A combined method segmentation method is proposed in this article. We use the orientation field information combined with statistical characteristics of gray. The Fingerprint Image realized the second segmentation with the method proposed in this paper. The experimental results show that the method used in this paper achieves a good effect.
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Research on Fingerprint Image Segmentation
Advanced Materials Research, 2012Co-Authors: Hong Wei LiAbstract:As part of Fingerprint Image pre-processing, Fingerprint Image segmentation plays an irreplaceable role. This paper proposes a method based on the orientation field information combined with statistical characteristics of gray in order to realize the second segmentation of Fingerprint Image. Various experimental results show that the method proposed in this paper improves the effect of segmentation.
Zhan Xiao-si - One of the best experts on this subject based on the ideXlab platform.
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Improved Fingerprint Image Segmentation Algorithm
Journal of Guangxi Normal University, 2020Co-Authors: Zhan Xiao-siAbstract:The Fingerprint segmentation algorithm based on gray variance can't segment those Fingerprint Images with high noise.After analyzing limitation of the Fingerprint Image segmentation algorithm based on gray variance,the paper proposes the improved algorithm to acquire the gray average and gray variance combining to the basic gray distributing character in the valid Fingerprint Image region.Experimental results indicate that the gray average and gray variance based on the improved algorithm are more representative of the original information of the Fingerprint Image region than the gray variance based on the classical algorithm.The segmented results of the algorithm proposed in the paper are more exact and reliable.
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New Method for Segmenting Fingerprint Image
Journal of Data Acquisition and Processing, 2020Co-Authors: Zhan Xiao-siAbstract:The two common means for segmenting the Fingerprint Image are variance method and direction method, which utilize its gray characteristic and direction information, respectively. After investigating and analyzing the two methods, this paper presents a new approach to segmenting the Fingerprint Image. For each block of the Image, two kinds of gray variations are calculated, one is horizontal to the orientation field and the other is vertical to that. Then these two kinds of gray variations aiming on the whole Image are normalized. To segment the Image, determine whether each block is a foreground area or a background area. This method fully utilizes the gray and direction characteristics of the Fingerprint Image, thus it can precisely separate the background area from the Fingerprint Image and the segmentation results are good.
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A Novel Fingerprint Image Binarization Algorithm Based on Orientation Information
Journal of Image and Graphics, 2020Co-Authors: Zhan Xiao-si, Sun Zhao-cai, Wang FengAbstract:Fingerprint Image binarization,as one key step of Fingerprint Image preprocessing,is the precondition of Fingerprint Image thinning.In order to utilize the texture character of the Fingerprint Image effectively,the paper introduces the orientation information in Fingerprint Image binarization.After considering the Fingerprint Image orientation information and self-adapt local threshold synthetically,this paper brings forward a kind of self-adapt local threshold binary algorithm using the orientation information.The contrastive experimental results indicate that the presented algorithm can achieve more exact binarization results than the self-adapt binarization algorithm.Moreover the algorithm can repair the disconnected line in the Fingerprint Image in a certain extent.The algorithm is important for improving the minutia extraction precision.
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A New Method of Fingerprint Image Enhancement
Journal of Fuyang Teachers College, 2020Co-Authors: Zhan Xiao-siAbstract:Fingerprint enhancement can improve the clarity of the ridge structures of input Fingerprint Images,and ensure the performance of the minutiae extraction and Fingerprint matching.In this paper,a new method of Fingerprint enhancement is proposed,based on Fourier transform and Gabor filter.Firstly,Fingerprint Image is transformed to freauency domain via the fast Fourier transform(FFT),then the Image is deived into n direction,in each of which direction Gabor filter is processed,and the finall Image is transformed via the negative Fourier transform.Tests with some Fingerprint Image show good performance of the method.
Fernando Alonso-Fernandez - One of the best experts on this subject based on the ideXlab platform.
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A Review Of Schemes For Fingerprint Image Quality Computation
2020Co-Authors: Fernando Alonso-Fernandez, Julian Fierrez-aguilar, Javier Ortega-garciaAbstract:Fingerprint Image quality affects heavily the performance of Fingerprint recognition systems. This paper reviews existing approaches for Fingerprint Image quality computation. We also implement, te ...
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A Comparative Study of Fingerprint Image-Quality Estimation Methods
IEEE Transactions on Information Forensics and Security, 2007Co-Authors: Fernando Alonso-Fernandez, Hartwig Fronthaler, Klaus Kollreider, Joaquin Gonzalez-rodriguez, Javier Ortega-garcia, Julian Fierrez, Josef BigunAbstract:One of the open issues in Fingerprint verification is the lack of robustness against Image-quality degradation. Poor-quality Images result in spurious and missing features, thus degrading the performance of the overall system. Therefore, it is important for a Fingerprint recognition system to estimate the quality and validity of the captured Fingerprint Images. In this work, we review existing approaches for Fingerprint Image-quality estimation, including the rationale behind the published measures and visual examples showing their behavior under different quality conditions. We have also tested a selection of Fingerprint Image-quality estimation algorithms. For the experiments, we employ the BioSec multimodal baseline corpus, which includes 19 200 Fingerprint Images from 200 individuals acquired in two sessions with three different sensors. The behavior of the selected quality measures is compared, showing high correlation between them in most cases. The effect of low-quality samples in the verification performance is also studied for a widely available minutiae-based Fingerprint matching system.