Fingerprint recognition using mel-frequency cepstral coefficients

Hashad, Fatma G.; Halim, T. M.; Diab, Salaheldin M.; Sallam, Bassiouny M.; El‐Samie, Fathi E. Abd

doi:10.1134/s1054661810030120

“…Cepstrum analysis is one of the standard and widely-used techniques used for speech processing applications. However, studies have also used cepstral analysis for 2D images and its implementations, e.g., face recognition [12], hand gesture recognition [13], fingerprint recognition [14], iris feature extraction [15], resolution enhancement [16], etc.…”

Section: The Proposed Cepstrum Analysismentioning

confidence: 99%

“…The work converted hand gesture images into 1D signal for extracting cepstral features and used support vector machine for classification. Hashad et al [14] used cepstral features for fingerprint recognition, while Barpanda et al [15] used wavelet cepstrum features for iris recognition. They extracted wavelet MFCC from the images.…”

Section: Introductionmentioning

confidence: 99%

A Framework for Crop Disease Detection Using Feature Fusion Method

Bhagwat

¹

,

Dandawate

²

2021

Int. j. eng. technol. innov.

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Crop disease detection methods vary from traditional machine learning, which uses Hand-Crafted Features (HCF) to the current deep learning techniques that utilize deep features. In this study, a hybrid framework is designed for crop disease detection using feature fusion. Convolutional Neural Network (CNN) is used for high level features that are fused with HCF. Cepstral coefficients of RGB images are presented as one of the features along with the other popular HCF. The proposed hybrid model is tested on the whole leaf images and also on the image patches which have individual lesions. The experimental results give an enhanced performance with a classification accuracy of 99.93% for the whole leaf images and 99.74% for the images with individual lesions. The proposed model also shows a significant improvement in comparison to the state-of-art techniques. The improved results show the prominence of feature fusion and establish cepstral coefficients as a pertinent feature for crop disease detection.

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“…The problem of fingerprint matching has been extensively studied and numerous algorithms have been proposed. These algorithms can be classified as correlation-based [3,4,5,6,7,9,8,10,11,12,13,14,15], minutiae-based [17,18,19,20] and frequency-based [21,22] approaches. Correlation-based matching is the most popular and widely used technique, being the basis of the fingerprint comparison.…”

Section: Introductionmentioning

confidence: 99%

Robust ﬁngerprint recognition approach based on diagonal slice of polyspectra in the polar space

Alaoui

2024

ELCVIA

0

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Although fingerprint recognition is a mature technology and nowadays commercial state-of-the-art systems can be successfully used in a number of real applications, not all the problems have been solved and the research is still very active in the field. This paper presents a new approach for estimating the shift and rotation parameters between fingerprint images stored in the dadabase that operates in the third-order frequency-domain measure called the auto-bispectrum, which, allows us to estimate the shift and the rotation separately. The diagonal slices and their spectra of auto- and cross-bispectrum are proposed. The rotation parameters are estimated from the remaining polar sampled the third-order spectrum using cross-correlation, and then, after compensating for rotation, we may easily estimate the translational component, e.g., by using phase correlation.Experimental evidence of this performance is presented, and the mathematical reasons behind these characteristics are explained in depth. We compare our approach in a simulation to other frequency-domain fingerprint recognition algorithms. We find that our algorithm can better estimate shift and rotation parameters than the other methods.

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“…The problem of fingerprint matching has been extensively studied and numerous algorithms have been proposed. These algorithms can be classified as correlation-based [1][2][3][4][5][6][7][8][9][10][11][12][13], minutiae-based [15][16][17][18] and frequency-based [19,20] approaches. Correlation-based matching is the most popular and widely used technique, being the basis of the fingerprint comparison.…”

Section: Introductionmentioning

confidence: 99%

Robust fingerprint recognition approach based on diagonal slice of polyspectra in the polar space

Alaoui

¹

2023

Preprint

0

View full text Add to dashboard Cite

Although fingerprint recognition is a mature technology and nowadays commercial state-of-the-art systems can be successfully used in a number of real applications, not all the problems have been solved and the research is still very active in the field. This paper presents a new approach for estimating the shift and rotation parameters between fingerprint images stored in the dadabase that operates in the third-order frequency-domain measure called the auto-bispectrum, which, allows us to estimate the shift and the rotation separately. The diagonal slices and their spectra of auto- and cross-bispectrum are proposed. The rotation parameters are estimated from the remaining polar sampled the third-order spectrum using cross-correlation, and then, after compensating for rotation, we may easily estimate the translational component, e.g., by using phase correlation.Experimental evidence of this performance is presented, and the mathematical reasons behind these characteristics are explained in depth. We compare our approach in a simulation to other frequency-domain fingerprint recognition algorithms. We find that our algorithm can better estimate shift and rotation parameters than the other methods.

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Fingerprint recognition using mel-frequency cepstral coefficients

Cited by 11 publications

References 13 publications

A Framework for Crop Disease Detection Using Feature Fusion Method

A Framework for Crop Disease Detection Using Feature Fusion Method

Robust ﬁngerprint recognition approach based on diagonal slice of polyspectra in the polar space

Robust fingerprint recognition approach based on diagonal slice of polyspectra in the polar space

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