Fingerprint Direct-Access Strategy Using Local-Star-Structure-based Discriminator Features: A Comparison Study

Indrawan, Gede; Akbar, Saiful; Sitohang, Benhard

doi:10.11591/ijece.v4i5.6589

Cited by 8 publications

(7 citation statements)

References 21 publications

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“…The selected data points along each radial line are known as radial resolution. The number of radial lines going around the iris region are known as radial resolution where the number of radial lines going around the iris region are defined as angular resolution [14].…”

Section: Normalizationmentioning

confidence: 99%

“…is the angle based on the edges were counted. r 1 is the radius of the iris [14]. The function first gives a 'doughnut' form to the iris region based on the angle.…”

Section: Withmentioning

confidence: 99%

“…Where ( − )is the kernel function, and are the input feature vectors, and σ is a parameter set by users to determine the effective width of the basis kernel function [14].…”

Section: Trainingmentioning

confidence: 99%

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A New Approach of Iris Detection and Recognition

Biswas¹,

Uddin²,

Hasan³

2017

IJECE

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This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen’s Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.

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Section: Normalizationmentioning

confidence: 99%

“…is the angle based on the edges were counted. r 1 is the radius of the iris [14]. The function first gives a 'doughnut' form to the iris region based on the angle.…”

Section: Withmentioning

confidence: 99%

See 1 more Smart Citation

A New Approach of Iris Detection and Recognition

Biswas¹,

Uddin²,

Hasan³

2017

IJECE

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“…Finally, the machine learning technique, Support Vector Machine (SVM) is used to classify the fingerprints efficiently. However, the recent performance comparison in the area of finger print depends on how far the accyracy, efficacy and scalability performance can be increased [8][9][10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A Novel 2D Feature Extraction Method for Fingerprints Using Minutiae Points and Their Intersections

Rakib¹,

Farhan²,

Sobhan³

et al. 2017

IJECE

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The field of biometrics has evolved tremendously for over the last century. Yet scientists are still continuing to come up with precise and efficient algorithms to facilitate automatic fingerprint recognition systems. Like other applications, an efficient feature extraction method plays an important role in fingerprint based recognition systems. This paper proposes a novel feature extraction method using minutiae points of a fingerprint image and their intersections. In this method, initially, it calculates the ridge ends and ridge bifurcations of each fingerprint image. And then, it estimates the minutiae points for the intersection of each ridge end and ridge bifurcation. In the experimental evaluation, we tested the extracted features of our proposed model using a support vector machine (SVM) classifier and experimental results show that the proposed method can accurately classify different fingerprint images.

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“…Based on our exploration results, Mel-Frequency Cepstral Coefficient (MFCC) feature does not have a structured pattern that represents the speaker's original characteristics. In addition, Indrawan et al proposed in [5,6] a direct access strategy for fingerprint identification system to improve the performance of the identification process. Indrawan's model uses a modified hash function for retrieving a candidate list based on fingerprint's local and global features.…”

Section: Introductionmentioning

confidence: 99%