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Papers by monji kherallah

Research paper thumbnail of Clothing Classification Using Deep CNN Architecture Based on Transfer Learning

Hybrid Intelligent Systems

Research paper thumbnail of Arabic handwriting recognition: Between handcrafted methods and deep learning techniques

2020 21st International Arab Conference on Information Technology (ACIT)

Research paper thumbnail of Contactless Heart Rate Estimation From Facial Video Using Skin Detection and Multi-resolution Analysis

This paper introduces a remote Photoplethysmography (rPPG), which is used to estimate human heart... more This paper introduces a remote Photoplethysmography (rPPG), which is used to estimate human heart rate withoutany physical contact, has been extensively applied in multiple fields like medical diagnosis, analysis of humanemotions, rehabilitation training programs, biometric, and fitness assessments. The rPPG signals are usually ex-tracted from facial videos. However, it is still a challenging task due to several contributing factors, e.g., variationin skin tone, lighting condition, and subject’s motion. Accordingly, in this work, a novel approach based on deeplearning skin detection method and the discrete wavelet transform (DWT) is employed to precisely estimate heartrate from facial videos. In the proposed method, by implementing the DWT, the signal is decomposed into approx-imations and details parts thereby it helps in analyzing it at different frequency bands with different resolutions.The results derived from the experiments show that our proposed method outperforms the state-...

Research paper thumbnail of Deep-Analysis of Palmprint Representation Based on Correlation Concept for Human Biometrics Identification

International Journal of Digital Crime and Forensics

The security of people requires a beefy guarantee in our society, particularly, with the spread o... more The security of people requires a beefy guarantee in our society, particularly, with the spread of terrorism throughout the world. In this context, palmprint identification based on texture analysis is amongst the pattern recognition applications to recognize people. In this article, the researchers investigated a deep texture analysis for the palmprint texture pattern representation based on a fusion between several texture information extractions through multiple descriptors, such as HOG and Gabor Filters, Fractal dimensions and GLCM corresponding respectively to the frequency, model, and statistical methodologies-based texture features. They assessed the proposed deep texture analysis method as well as the applicability of the dimensionality reduction techniques and the correlation concept between the features-based fusion on the challenging PolyU, CASIA and IIT-Delhi Palmprint databases. The experimental results show that the fusion of different texture types using the correlati...

Research paper thumbnail of Improving the DBLSTM for on-line Arabic handwriting recognition

Multimedia Tools and Applications

Research paper thumbnail of Boosting of Deep Convolutional Architectures for Arabic Handwriting Recognition

International Journal of Multimedia Data Engineering and Management

In recent years, deep learning (DL) based systems have become very popular for constructing hiera... more In recent years, deep learning (DL) based systems have become very popular for constructing hierarchical representations from unlabeled data. Moreover, DL approaches have been shown to exceed foregoing state of the art machine learning models in various areas, by pattern recognition being one of the more important cases. This paper applies Convolutional Deep Belief Networks (CDBN) to textual image data containing Arabic handwritten script (AHS) and evaluated it on two different databases characterized by the low/high-dimension property. In addition to the benefits provided by deep networks, the system is protected against over-fitting. Experimentally, the authors demonstrated that the extracted features are effective for handwritten character recognition and show very good performance comparable to the state of the art on handwritten text recognition. Yet using Dropout, the proposed CDBN architectures achieved a promising accuracy rates of 91.55% and 98.86% when applied to IFN/ENIT ...

Research paper thumbnail of Multi-language online handwriting recognition based on beta-elliptic model and hybrid TDNN-SVM classifier

Multimedia Tools and Applications

Research paper thumbnail of Recognizing online Arabic handwritten characters using a deep architecture

Ninth International Conference on Machine Vision (ICMV 2016)

Research paper thumbnail of Palmprint recognition through the fractal dimension estimation for texture analysis

International Journal of Biometrics, 2016

Research paper thumbnail of Window-based feature extraction framework for machine-printed/handwritten and Arabic/Latin text discrimination

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), 2016

Research paper thumbnail of Combining shape analysis and texture pattern for palmprint identification

Multimedia Tools and Applications, 2016

Research paper thumbnail of Biometric Palmprint identification via efficient texture features fusion

2016 International Joint Conference on Neural Networks (IJCNN), 2016

Research paper thumbnail of Offline Arabic Handwritten recognition system with dropout applied in Deep networks based-SVMs

2016 International Joint Conference on Neural Networks (IJCNN), 2016

Research paper thumbnail of On-Line Recognition Of Handwritten Digits Based On Trajectory And Velocity Modelling

... depends on the goal of the research. The trajectory/velocity modeling techniques were many ye... more ... depends on the goal of the research. The trajectory/velocity modeling techniques were many years ago applied in the handwriting modeling field (Morasso et al in 198X, Plamondon et al in 199X, Alimi et al in 199X etc…) [1-5, 39, 40, 42-44]. ... 4. Update: ( ) 2 2 max ji ji jj* i ji 1 2 1 ...

Research paper thumbnail of A novel architecture of CNN based on SVM classifier for recognising Arabic handwritten script

International Journal of Intelligent Systems Technologies and Applications, 2016

Research paper thumbnail of Graphemes Segmentation for Arabic Online Handwriting Modeling

Journal of Information Processing Systems, 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling repre... more In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

Research paper thumbnail of Feature Extractor Based Deep Method to Enhance Online Arabic Handwritten Recognition System

Lecture Notes in Computer Science, 2016

Research paper thumbnail of Improving MDLSTM for Offline Arabic Handwriting Recognition Using Dropout at Different Positions

Lecture Notes in Computer Science, 2016

Research paper thumbnail of A New Design Based-SVM of the CNN Classifier Architecture with Dropout for Offline Arabic Handwritten Recognition

Procedia Computer Science, 2016

Research paper thumbnail of Fractal and Multi-fractal for Arabic Offline Writer Identification

2010 20th International Conference on Pattern Recognition, 2010

... Machines University of Sfax, National School of Engineers (ENIS) BP 1173, Sfax, 3038, Tunisia... more ... Machines University of Sfax, National School of Engineers (ENIS) BP 1173, Sfax, 3038, Tunisia {ayman.chaabouni,houcine-boubaker,monji ... Said, GS Peake, TN Tan and KD Baker, Writer identification from non-uniformly skewed handwriting images . ... [14] S. Ben Moussaa, A ...

Research paper thumbnail of Clothing Classification Using Deep CNN Architecture Based on Transfer Learning

Hybrid Intelligent Systems

Research paper thumbnail of Arabic handwriting recognition: Between handcrafted methods and deep learning techniques

2020 21st International Arab Conference on Information Technology (ACIT)

Research paper thumbnail of Contactless Heart Rate Estimation From Facial Video Using Skin Detection and Multi-resolution Analysis

This paper introduces a remote Photoplethysmography (rPPG), which is used to estimate human heart... more This paper introduces a remote Photoplethysmography (rPPG), which is used to estimate human heart rate withoutany physical contact, has been extensively applied in multiple fields like medical diagnosis, analysis of humanemotions, rehabilitation training programs, biometric, and fitness assessments. The rPPG signals are usually ex-tracted from facial videos. However, it is still a challenging task due to several contributing factors, e.g., variationin skin tone, lighting condition, and subject’s motion. Accordingly, in this work, a novel approach based on deeplearning skin detection method and the discrete wavelet transform (DWT) is employed to precisely estimate heartrate from facial videos. In the proposed method, by implementing the DWT, the signal is decomposed into approx-imations and details parts thereby it helps in analyzing it at different frequency bands with different resolutions.The results derived from the experiments show that our proposed method outperforms the state-...

Research paper thumbnail of Deep-Analysis of Palmprint Representation Based on Correlation Concept for Human Biometrics Identification

International Journal of Digital Crime and Forensics

The security of people requires a beefy guarantee in our society, particularly, with the spread o... more The security of people requires a beefy guarantee in our society, particularly, with the spread of terrorism throughout the world. In this context, palmprint identification based on texture analysis is amongst the pattern recognition applications to recognize people. In this article, the researchers investigated a deep texture analysis for the palmprint texture pattern representation based on a fusion between several texture information extractions through multiple descriptors, such as HOG and Gabor Filters, Fractal dimensions and GLCM corresponding respectively to the frequency, model, and statistical methodologies-based texture features. They assessed the proposed deep texture analysis method as well as the applicability of the dimensionality reduction techniques and the correlation concept between the features-based fusion on the challenging PolyU, CASIA and IIT-Delhi Palmprint databases. The experimental results show that the fusion of different texture types using the correlati...

Research paper thumbnail of Improving the DBLSTM for on-line Arabic handwriting recognition

Multimedia Tools and Applications

Research paper thumbnail of Boosting of Deep Convolutional Architectures for Arabic Handwriting Recognition

International Journal of Multimedia Data Engineering and Management

In recent years, deep learning (DL) based systems have become very popular for constructing hiera... more In recent years, deep learning (DL) based systems have become very popular for constructing hierarchical representations from unlabeled data. Moreover, DL approaches have been shown to exceed foregoing state of the art machine learning models in various areas, by pattern recognition being one of the more important cases. This paper applies Convolutional Deep Belief Networks (CDBN) to textual image data containing Arabic handwritten script (AHS) and evaluated it on two different databases characterized by the low/high-dimension property. In addition to the benefits provided by deep networks, the system is protected against over-fitting. Experimentally, the authors demonstrated that the extracted features are effective for handwritten character recognition and show very good performance comparable to the state of the art on handwritten text recognition. Yet using Dropout, the proposed CDBN architectures achieved a promising accuracy rates of 91.55% and 98.86% when applied to IFN/ENIT ...

Research paper thumbnail of Multi-language online handwriting recognition based on beta-elliptic model and hybrid TDNN-SVM classifier

Multimedia Tools and Applications

Research paper thumbnail of Recognizing online Arabic handwritten characters using a deep architecture

Ninth International Conference on Machine Vision (ICMV 2016)

Research paper thumbnail of Palmprint recognition through the fractal dimension estimation for texture analysis

International Journal of Biometrics, 2016

Research paper thumbnail of Window-based feature extraction framework for machine-printed/handwritten and Arabic/Latin text discrimination

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP), 2016

Research paper thumbnail of Combining shape analysis and texture pattern for palmprint identification

Multimedia Tools and Applications, 2016

Research paper thumbnail of Biometric Palmprint identification via efficient texture features fusion

2016 International Joint Conference on Neural Networks (IJCNN), 2016

Research paper thumbnail of Offline Arabic Handwritten recognition system with dropout applied in Deep networks based-SVMs

2016 International Joint Conference on Neural Networks (IJCNN), 2016

Research paper thumbnail of On-Line Recognition Of Handwritten Digits Based On Trajectory And Velocity Modelling

... depends on the goal of the research. The trajectory/velocity modeling techniques were many ye... more ... depends on the goal of the research. The trajectory/velocity modeling techniques were many years ago applied in the handwriting modeling field (Morasso et al in 198X, Plamondon et al in 199X, Alimi et al in 199X etc…) [1-5, 39, 40, 42-44]. ... 4. Update: ( ) 2 2 max ji ji jj* i ji 1 2 1 ...

Research paper thumbnail of A novel architecture of CNN based on SVM classifier for recognising Arabic handwritten script

International Journal of Intelligent Systems Technologies and Applications, 2016

Research paper thumbnail of Graphemes Segmentation for Arabic Online Handwriting Modeling

Journal of Information Processing Systems, 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling repre... more In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

Research paper thumbnail of Feature Extractor Based Deep Method to Enhance Online Arabic Handwritten Recognition System

Lecture Notes in Computer Science, 2016

Research paper thumbnail of Improving MDLSTM for Offline Arabic Handwriting Recognition Using Dropout at Different Positions

Lecture Notes in Computer Science, 2016

Research paper thumbnail of A New Design Based-SVM of the CNN Classifier Architecture with Dropout for Offline Arabic Handwritten Recognition

Procedia Computer Science, 2016

Research paper thumbnail of Fractal and Multi-fractal for Arabic Offline Writer Identification

2010 20th International Conference on Pattern Recognition, 2010

... Machines University of Sfax, National School of Engineers (ENIS) BP 1173, Sfax, 3038, Tunisia... more ... Machines University of Sfax, National School of Engineers (ENIS) BP 1173, Sfax, 3038, Tunisia {ayman.chaabouni,houcine-boubaker,monji ... Said, GS Peake, TN Tan and KD Baker, Writer identification from non-uniformly skewed handwriting images . ... [14] S. Ben Moussaa, A ...