Enhanced Local Binary Patterns for Automatic Face Recognition

Král, Pavel; Vrba, Antonín; Lenc, Ladislav

doi:10.1007/978-3-030-20915-5_3

“…Similar studies were carried out with different methods, and different results were obtained. The method used here is very widely used, especially in areas such as face recognition and image classification (Král, Vrba & Lenc, 2019;Hassaballah, Alshazly & Ali, 2019;Wang et al, 2019;Aberni, Boubchir & Daachi, 2020).…”

Section: Discussionmentioning

confidence: 99%

Ses Kullanarak Otomatik Yerel İkili Model Yöntemi ile Gemi Tanımlama

Tuncer¹,

Aydemir²

2020

ACIN

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Sound classification is one of the most important areas of research for mechanics and applied computer sciences. Using the sound classification method, many biometric applications/methods have been presented in the literature. This study presents a ship identification method using sounds. The method presented here is very simple and effective. It has only two fundamental phases and these are feature extraction by one dimensional binary pattern (1D-BP) and classification with conventional classifiers phases. 1D-BP extracts 256 features from each sound and these sounds are forwarded to classifiers. To test this ultra-lightweight sound identification method, a ship sounds dataset was collected from YouTube. According to our results, this method achieved a 97% classification accuracy. This result clearly demonstrates the merits of the 1D-BP based on ship sound classification method and the sound-based ship identification method which we present here.

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“…To increase the efficiency of the CBIR system for face recognition, many researchers have proposed some more variants of LBP. These includes Extended local binary pattern (ELBP) [10], Local Neighbourhood Intensity Pattern (LNIP) [26], Improved LBP (ILBP) [27], Enhanced Local Binary Patterns (E-LBP) [28], Local directional edge binary pattern (LDEBP) [29], directional local ternary co-occurrence pattern (DLTCoP) [30], Graph-Based Structure Binary Pattern (GBSBP) [31], Multi-scale neighbourhood basedtree binary pattern (MNB-TBP) [32], Most significant bits based local binary pattern (m-LBP) [33], Local directional peak valley binary pattern has been presented in [34] etc. This research paper presents a novel LBP variant called Mean-Variance and Median based LBP (MVM-LBP) for face recognition.…”

Section: Related Workmentioning

confidence: 99%

MVM-LBP : mean−variance−median based LBP for face recognition

Arora

¹

,

Sucharitha

²

,

Sharma

³

2023

Int. j. inf. tecnol.

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This paper proposes a novel descriptor called Mean-Variance-Median based LBP (MVM-LBP). The Median binary pattern (MBP) calculates the difference between median of all the pixels in a 3 × 3 pixel window and respective eight neighbours is used. The main draw back of MBP is that two different pixel windows can have same MBP code which is not appropriate in face recognition systems. To improve the performance of the system, the proposed descriptor (MVM-LBP) involves more statistics and uses the mean, variance, and median values of all the pixels in a 3 × 3 pixel window to get a more robust feature vector. To check the excellence the of the proposed descriptor, the proposed method is applied on two publicly available facial data sets AT&T, and faces94. The outcomes show that the proposed descriptor gives encouraging results.

show abstract

“…To increase the efficiency of the CBIR system for face recognition, many researchers have proposed some more variants of LBP. These includes Extended local binary pattern (ELBP) [10], Local Neighbourhood Intensity Pattern (LNIP) [26], Improved LBP (ILBP) [27], Enhanced Local Binary Patterns (E-LBP) [28], Local directional edge binary pattern (LDEBP) [29], directional local ternary co-occurrence pattern (DLTCoP) [30], Graph-Based Structure Binary Pattern (GBSBP) [31], Multi-scale neighbourhood basedtree binary pattern (MNB-TBP) [32], Most significant bits based local binary pattern (m-LBP) [33], Local directional peak valley binary pattern has been presented in [34] etc. This research paper presents a novel LBP variant called Mean-Variance and Median based LBP (MVM-LBP) for face recognition.…”

Section: Related Workmentioning

confidence: 99%

MVM-LBP: Mean−Variance−Median based LBP for face recognition

Arora

¹

,

Sucharitha²,

Sharma

³

2022

Preprint

1

0

View full text Add to dashboard Cite

This paper proposes a novel descriptor called Mean-Variance-Median based LBP (MVM-LBP). The Median binary pattern (MBP) calculates the difference between median of all the pixels in a 3 × 3 pixel window and respective eight neighbours is used. The main draw back of MBP is that two different pixel windows can have same MBP code which is not appropriate in face recognition systems. To improve the performance of the system, the proposed descriptor (MVM-LBP) involves more statistics and uses the mean, variance, and median values of all the pixels in a 3 × 3 pixel window to get a more robust feature vector. To check the excellence the of the proposed descriptor, the proposed method is applied on two publicly available facial data sets AT&T, and faces94. The outcomes show that the proposed descriptor gives encouraging results.

show abstract

Enhanced Local Binary Patterns for Automatic Face Recognition

Cited by 9 publications

References 15 publications

Ses Kullanarak Otomatik Yerel İkili Model Yöntemi ile Gemi Tanımlama

Ses Kullanarak Otomatik Yerel İkili Model Yöntemi ile Gemi Tanımlama

MVM-LBP : mean−variance−median based LBP for face recognition

MVM-LBP: Mean−Variance−Median based LBP for face recognition

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