Palmprint Recognition Using Fusion of 2D-Gabor and 2D Log-Gabor Features

Prasad, Munaga V. N. K.; Kavati, Ilaiah; Adinarayana, B.

doi:10.1007/978-3-642-54525-2_18

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…Because of time/space and frequency invariance, symmetry on the log frequency axis, Log-Gabor filter has systematically investigated and applied for texture based feature extraction [27]. The Log Gabor filter has applied by using the following formula [25,26]:…”

Section: D-log Gabor Filtermentioning

confidence: 99%

Designing Efficient Feature Space Reduction Schemes for Multi-Algorithmic Iris Recognition System based on Feature Level Fusion of Texture and Phase Features

Kumari*¹,

Suma²

2019

IJRTE

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Iris recognition system has gained prominent focus because of its uniqueness, stability over time. But the recognition level of single biometric based recognition systems is greatly affected by environmental conditions, physiological deficiency. Multi-biometric systems diminish this problem with the fusion of features collected from various traits or samples of the same trait, a single trait by employing multiple algorithms or multiple instances. To gain the advantages of multi-biometric systems in iris recognition, a Multi-algorithmic iris recognition system has been proposed where Texture features from iris are extracted by using 2D-Log Gabor filter and Phase features are extracted by Haar Wavelet; And these features can be integrated at various levels like Decision, Rank, Score, feature, and pixel. Even though the feature level fusion contains rich information about biometric samples when compared to remaining fusion levels; it involves mapping complexity, high dimensional feature space. To gain advantage of feature level fusion in iris recognition and to overcome the problem of resulted high dimensional feature space, Genetic Algorithm (GA) based reduction scheme, Principal Component Analysis (PCA) reduction strategy and a hybrid reduction scheme which is a combination of PCA and GA have been applied to reduce the resulted feature space. The performance of these reduction strategies have evaluated on CASIA iris database, IIT Delhi iris database using Machine Learning approaches. The results have shown that the feature space has dramatically reduced while keeping recognition accuracy and also revealed that space and time requirements have significantly decreased after employing feature reduction schemes.

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Section: D-log Gabor Filtermentioning

confidence: 99%

Designing Efficient Feature Space Reduction Schemes for Multi-Algorithmic Iris Recognition System based on Feature Level Fusion of Texture and Phase Features

Kumari*¹,

Suma²

2019

IJRTE

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A Robust Method for Multi-algorithmic Palmprint Recognition Using Exponential Genetic Algorithm-Based Feature Selection

Palisetty¹,

Gogulamanda²

2020

Communication Software and Networks

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Local Feature Integration Method Using Phase Congruency for Palm Print Authentication

Latha¹,

Prasad

Sammulal

2015

Int. J. Image Grap.

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Palm print authentication is a biometric technology to identify a person's identity. In this paper, phase congruency method is used to extract features from palm print ROI images. The phase congruency is an efficient method to extract features at varying illumination condition and the image is invariant to contrast. By applying this method, local phase congruency (LPC), local orientation (LO) and local phase (LP) are extracted individually and fused using score level fusion. To reduce false acceptance rate (FAR), Min-Max threshold range is employed and the proposed method is tested on PolyU database of 7480 images from 374 individuals, with 20 image samples per individual. The proposed system achieves genuine acceptance rate (GAR) of 100% and FAR of 0.65%.

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Palmprint Recognition Using Fusion of 2D-Gabor and 2D Log-Gabor Features

Cited by 3 publications

References 19 publications

Designing Efficient Feature Space Reduction Schemes for Multi-Algorithmic Iris Recognition System based on Feature Level Fusion of Texture and Phase Features

Designing Efficient Feature Space Reduction Schemes for Multi-Algorithmic Iris Recognition System based on Feature Level Fusion of Texture and Phase Features

A Robust Method for Multi-algorithmic Palmprint Recognition Using Exponential Genetic Algorithm-Based Feature Selection

Local Feature Integration Method Using Phase Congruency for Palm Print Authentication

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