Fingerprint verification based on fixed length square finger code

Patil, Pradeep M.; Suralkar, S. R.; Abhyankar, Hemant K.

doi:10.1109/ictai.2005.66

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…To capture the texture information of fingerprint image, Gabor filter with eight orientations is proposed by Jain et al [12]. Patil et al [13] used four orientations of Gabor filters for extracting fingerprint features from gray scale fingerprint image. The image is cropped to the size of 128 × 128 pixels using its core point as the center.…”

Section: Introductionmentioning

confidence: 99%

Online Fingerprint Verification Algorithm and Distributed System

Zhang¹,

Guo²,

Gadedadikar³

2011

JSIP

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In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset

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Section: Introductionmentioning

confidence: 99%

Online Fingerprint Verification Algorithm and Distributed System

Zhang¹,

Guo²,

Gadedadikar³

2011

JSIP

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“…Hence, one of the critical processes is to locate the core-point correctly and efficiently, which is very important to the classifying and matching process. Many methods for locating its core-point have been developed including [2]- [6] and so on.…”

Section: Introductionmentioning

confidence: 99%

Core-Point Location Method Using Image Sampling Techniques

Ya-sha¹,

Wu²

2007

2007 1st International Conference on Bioinformatics and Biomedical Engineering

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With an increasing emphasis on the personal identification applications, fingerprint-based identification has received a lot of attention. This paper presents a core-point location method and analyzes its performance. In the proposed algorithm, Fast Fourier Transform is applied to preprocess the fingerprint, and then the image is sampled to form four normalization levels step by step, the coordinate of the core is calculated and showed in the reconstructed image. Finally, an illustrative example is given to prove that it is easy to realize the discrimination performance of the identification algorithm.

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An effective algorithm for fingerprint reference point detection based on filed flow curves

Nasiri

2015

2015 the International Symposium on Artificial Intelligence and Signal Processing (AISP)

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In this paper a novel approach is proposed to detect reference point for fingerprint images. Reference point extraction is a key component in automatic fingerprint identification and recognition systems. A new method was proposed for fingerprint reference point extraction, based on field flow curve and clustering. High curvature points in the flow curves are used in our reference point detection. Because we use flow curve instead of ridge for reference point detection, our method is robust to noise and has a good result on fingerprint image with low quality. Also our method has the ability to detect a reference point for an arch class fingerprint which is hard for other methods to detect it. The experiments are conducted on FVC2002-DB2a and FVC2004 to measure the performance of our reference point detection. Experimental results show that our algorithm is robust and it has better results than other approaches. Index Terms-Orientation field, reference point, filed flow curve, curvature, single-link clustering, Poincare index.

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Fingerprint verification based on fixed length square finger code

Cited by 6 publications

References 12 publications

Online Fingerprint Verification Algorithm and Distributed System

Online Fingerprint Verification Algorithm and Distributed System

Core-Point Location Method Using Image Sampling Techniques

An effective algorithm for fingerprint reference point detection based on filed flow curves

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