faiq baji - Academia.edu (original) (raw)

Papers by faiq baji

2018 International Conference on Development and Application Systems (DAS)

The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important... more The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important step in the diagnosis of brain pathologies and calculation of the symmetry between the two sides of a MSP. In this paper, a new method is proposed to locate MSP in T1-weighted MRI images, based on the computation of the different local texture between inter-hemispheric fissure (IF) region and the surrounding tissue. This method is based on local binary pattern technique. It is high-performance texture features to describe local structures. However, the LBP method is sensitive to noise. To overcome this disadvantage, we proposed a new method by using Block Local Ternary Patterns for achieving high classification accuracy thus improving the encoding of the texture feature. The proposed method is based on the second-moments method to solve the tilted brain problem; the rotation angle resulted is used to determine the initial line of the MSP. The performances of the proposed method are compared with the two extensions of LBP features, average LBP and block-based LBP. As it can be seen from the experimental data, the efficiency of the proposed method is better in comparison to the traditional LBP techniques in terms of classification accuracy.

Bulletin of Electrical Engineering and Informatics

Tumors in brains are caused by the unregulated emergence of tissue cells inside the brain. The ea... more Tumors in brains are caused by the unregulated emergence of tissue cells inside the brain. The early diagnosis and determining the precise location of the tumor in magnetic resonance imaging (MRI) and its size are essential for the teams of physicians. Image segmentation is often considered a preliminary step in medical image analyses. K-means clustering has been widely adopted for brain tumor detection. The result of this technique is a list of cluster images. The challenge of this method is the difficulty of selecting the appropriate cluster section that depicts the tumor. In this work, we analyze the influence of different image clusters. Each cluster is then split into the left and right parts. After that, the texture features are depicted in each part. Furthermore, the bilateral symmetry measure is applied to estimate the cluster that contains the tumor. Finally, the connected component labeling is employed to determine the target cluster for brain tumor detection. The develope...

The growth of information technology and data transfer led to increase the data attacks, so that ... more The growth of information technology and data transfer led to increase the data attacks, so that information security becomes an important issue to keep the data saved during information exchanges in computer networks. Steganography techniques used to protect the information from being detected. The art of steganography will hide secret information into cover data, which will be sending without any change so the attack does not recognize any change into cover image. This paper use the Steganography and artificial neural networks to presents an information hiding procedure for hiding text in cover image, the secret text will be converted to binary code, also the cover image will be converted to the binary data in form of vectors. The supervised learning of neural networks will use binary patterns of hidden text as set of input values, and the corresponding cover image data as target that used as teacher signal to neural network. The generated weights from neural network and the coord...

2018 International Conference on Development and Application Systems (DAS), 2018

The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important... more The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important step in the diagnosis of brain pathologies and calculation of the symmetry between the two sides of a MSP. In this paper, a new method is proposed to locate MSP in T1-weighted MRI images, based on the computation of the different local texture between inter-hemispheric fissure (IF) region and the surrounding tissue. This method is based on local binary pattern technique. It is high-performance texture features to describe local structures. However, the LBP method is sensitive to noise. To overcome this disadvantage, we proposed a new method by using Block Local Ternary Patterns for achieving high classification accuracy thus improving the encoding of the texture feature. The proposed method is based on the second-moments method to solve the tilted brain problem; the rotation angle resulted is used to determine the initial line of the MSP. The performances of the proposed method are comp...

2017 18th International Carpathian Control Conference (ICCC), 2017

With the popularity of the network and expansion of multimedia technology, the traditional techni... more With the popularity of the network and expansion of multimedia technology, the traditional techniques of information retrieval do not satisfy the requirements of users. Recently, the content based image retrieval and its techniques have become the hot topic to satisfy a great development. In this paper, a new method is proposed to solve the problem of regions of interest (ROI) based image retrieval. The ROI technique which is based on segmenting the image into fixed partitions is computationally costly. The proposed method is based on the connected components and interesting of objects to generate the histogram and statistical texture feature vectors. These resulted vectors are used to retrieve images from a large image database. The color and texture features of the connected components are computed from the histograms of the quantized HSV color space and Gray Level Co-occurrence Matrix (GLCM), respectively. The vectors matching process is based on the histogram intersection. It is...

Engineering and Technology Journal, 2012

The growth of information technology and data transfer led to increase the data attacks, so that ... more The growth of information technology and data transfer led to increase the data attacks, so that information security becomes an important issue to keep the data saved during information exchanges in computer networks. Steganography techniques used to protect the information from being detected. The art of steganography will hide secret information into cover data, which will be sending without any change so the attack does not recognize any change into cover image. This paper use the Steganography and artificial neural networks to presents an information hiding procedure for hiding text in cover image, the secret text will be converted to binary code, also the cover image will be converted to the binary data in form of vectors. The supervised learning of neural networks will use binary patterns of hidden text as set of input values, and the corresponding cover image data as target that used as teacher signal to neural network. The generated weights from neural network and the coord...

Indian Journal of Science and Technology, 2018

Journal of Engineering Science and Technology, 2018

The brain is one of the largest and most complex organs of the human body. The brain can be a vic... more The brain is one of the largest and most complex organs of the human body. The brain can be a victim of numerous pathologies, including malignant tumours, strokes, infection, head injuries, and diseases. Brain tumour extraction and analysis are challenging tasks for medical image processing due to the complexity of images. Since the growth of tumours causes asymmetry in the affected parts of the brain, the proposed method calculates asymmetry based on the intensity difference between the left and right of a Mid-Sagittal Plane (MSP). One of the problems of this method appears when the brain object is rotated or tilted. A new method is proposed to solve this problem, by locating the MidSagittal Plane in T1-weighted MRI images, based on the low intensity of InterHemispheric Fissure (IF) region. In this paper, we have proposed segmentation of the brain MRI image using K-means clustering algorithm followed by a connected component label to determine the location and size of a tumour. The...

Deep learning have gained lately popularity by achieving very good results for recognizing object... more Deep learning have gained lately popularity by achieving very good results for recognizing objects such as cars, plants, coffee cups in images. Big companies like Facebook, Google, Amazon are already using these methods to identify faces, recognize voice commands and even enable self-driving cars. Deep learning is based on classical neural networks and represents a method of machine learning and has evolved over the years to become a research field on its own. Deep neural networks are based on different models: Stacked Auto Encoder ,Deep Belief Networks, Deep Boltzmann Machine ,Convolutional Neural Networks, Recurrent Neural Networks. Most deep learning researchers are not programming neural networks directly but, they are using software libraries like: TensorFlow, Caffe2, Theano, Torch, etc. Deep learning is a central method for developing new applications in medical sector. Medical sector has access to vast quantities of patient data and images can be fed in the deep learning neur...

The brain is one of the largest and most complex organs of the human body. The brain can be a vic... more The brain is one of the largest and most complex organs of the human body. The brain can be a victim of numerous pathologies, including malignant tumours, strokes, infection, head injuries, and diseases. Brain tumour extraction and analysis are challenging tasks for medical image processing due to the complexity of images. Since the growth of tumours causes asymmetry in the affected parts of the brain, the proposed method calculates asymmetry based on the intensity difference between the left and right of a Mid-Sagittal Plane (MSP). One of the problems of this method appears when the brain object is rotated or tilted. A new method is proposed to solve this problem, by locating the MidSagittal Plane in T1-weighted MRI images, based on the low intensity of InterHemispheric Fissure (IF) region. In this paper, we have proposed segmentation of the brain MRI image using K-means clustering algorithm followed by a connected component label to determine the location and size of a tumour. The...

2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)

2009 Second International Conference on Computer and Electrical Engineering, 2009

The protection of ownership and the protection of unauthorized tampering of multimedia data (audi... more The protection of ownership and the protection of unauthorized tampering of multimedia data (audio, image, video, and document) have become a major concern for the authors of multimedia. Image authentication verifies the originality of an image by detecting malicious manipulation. The protection of ownership and the protection of unauthorized tampering of multimedia data (audio, image, video, and document) have become a major concern for the authors of multimedia. Image authentication verifies the originality of an image by detecting malicious manipulations. Digital watermarking researches have generally focused on two classes of watermarks, fragile and robust. Fragile watermarks are used for authentication purposes and are capable of detecting even minute changes of the water marked images. Robust watermarks are designed to be detected even when attempts are made to remove them. In this paper, we focus on the first class of watermarking for digital images authentication by creating a mark based on the self similarities blocks properties of fractal encoding. We start with fractal encoding algorithm, then, partitioning the tested image into ranges and domains blocks, finding the pieces of ranges and their corresponding domains by minimizing the distances between them, finally, we create the mark by partitioning the same image into four columns of equal size and compute the mark through the determination of location for domain block parameters in which column number occurs.

Indian Journal of Science and Technology, 2018

Shape recognition is the most important issue in image understanding and computer vision. Shape r... more Shape recognition is the most important issue in image understanding and computer vision. Shape representation is a primary issue in shape recognition. The rotation angle of the object and the similarity between the horizontally/ vertically flipping shapes and the original shape

2018 International Conference on Development and Application Systems (DAS)

The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important... more The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important step in the diagnosis of brain pathologies and calculation of the symmetry between the two sides of a MSP. In this paper, a new method is proposed to locate MSP in T1-weighted MRI images, based on the computation of the different local texture between inter-hemispheric fissure (IF) region and the surrounding tissue. This method is based on local binary pattern technique. It is high-performance texture features to describe local structures. However, the LBP method is sensitive to noise. To overcome this disadvantage, we proposed a new method by using Block Local Ternary Patterns for achieving high classification accuracy thus improving the encoding of the texture feature. The proposed method is based on the second-moments method to solve the tilted brain problem; the rotation angle resulted is used to determine the initial line of the MSP. The performances of the proposed method are compared with the two extensions of LBP features, average LBP and block-based LBP. As it can be seen from the experimental data, the efficiency of the proposed method is better in comparison to the traditional LBP techniques in terms of classification accuracy.

Bulletin of Electrical Engineering and Informatics

Tumors in brains are caused by the unregulated emergence of tissue cells inside the brain. The ea... more Tumors in brains are caused by the unregulated emergence of tissue cells inside the brain. The early diagnosis and determining the precise location of the tumor in magnetic resonance imaging (MRI) and its size are essential for the teams of physicians. Image segmentation is often considered a preliminary step in medical image analyses. K-means clustering has been widely adopted for brain tumor detection. The result of this technique is a list of cluster images. The challenge of this method is the difficulty of selecting the appropriate cluster section that depicts the tumor. In this work, we analyze the influence of different image clusters. Each cluster is then split into the left and right parts. After that, the texture features are depicted in each part. Furthermore, the bilateral symmetry measure is applied to estimate the cluster that contains the tumor. Finally, the connected component labeling is employed to determine the target cluster for brain tumor detection. The develope...

The growth of information technology and data transfer led to increase the data attacks, so that ... more The growth of information technology and data transfer led to increase the data attacks, so that information security becomes an important issue to keep the data saved during information exchanges in computer networks. Steganography techniques used to protect the information from being detected. The art of steganography will hide secret information into cover data, which will be sending without any change so the attack does not recognize any change into cover image. This paper use the Steganography and artificial neural networks to presents an information hiding procedure for hiding text in cover image, the secret text will be converted to binary code, also the cover image will be converted to the binary data in form of vectors. The supervised learning of neural networks will use binary patterns of hidden text as set of input values, and the corresponding cover image data as target that used as teacher signal to neural network. The generated weights from neural network and the coord...

2018 International Conference on Development and Application Systems (DAS), 2018

The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important... more The detection and localization of the mid-sagittal plane (MSP) in brain MR images is an important step in the diagnosis of brain pathologies and calculation of the symmetry between the two sides of a MSP. In this paper, a new method is proposed to locate MSP in T1-weighted MRI images, based on the computation of the different local texture between inter-hemispheric fissure (IF) region and the surrounding tissue. This method is based on local binary pattern technique. It is high-performance texture features to describe local structures. However, the LBP method is sensitive to noise. To overcome this disadvantage, we proposed a new method by using Block Local Ternary Patterns for achieving high classification accuracy thus improving the encoding of the texture feature. The proposed method is based on the second-moments method to solve the tilted brain problem; the rotation angle resulted is used to determine the initial line of the MSP. The performances of the proposed method are comp...

2017 18th International Carpathian Control Conference (ICCC), 2017

With the popularity of the network and expansion of multimedia technology, the traditional techni... more With the popularity of the network and expansion of multimedia technology, the traditional techniques of information retrieval do not satisfy the requirements of users. Recently, the content based image retrieval and its techniques have become the hot topic to satisfy a great development. In this paper, a new method is proposed to solve the problem of regions of interest (ROI) based image retrieval. The ROI technique which is based on segmenting the image into fixed partitions is computationally costly. The proposed method is based on the connected components and interesting of objects to generate the histogram and statistical texture feature vectors. These resulted vectors are used to retrieve images from a large image database. The color and texture features of the connected components are computed from the histograms of the quantized HSV color space and Gray Level Co-occurrence Matrix (GLCM), respectively. The vectors matching process is based on the histogram intersection. It is...

Engineering and Technology Journal, 2012

The growth of information technology and data transfer led to increase the data attacks, so that ... more The growth of information technology and data transfer led to increase the data attacks, so that information security becomes an important issue to keep the data saved during information exchanges in computer networks. Steganography techniques used to protect the information from being detected. The art of steganography will hide secret information into cover data, which will be sending without any change so the attack does not recognize any change into cover image. This paper use the Steganography and artificial neural networks to presents an information hiding procedure for hiding text in cover image, the secret text will be converted to binary code, also the cover image will be converted to the binary data in form of vectors. The supervised learning of neural networks will use binary patterns of hidden text as set of input values, and the corresponding cover image data as target that used as teacher signal to neural network. The generated weights from neural network and the coord...

Indian Journal of Science and Technology, 2018

Journal of Engineering Science and Technology, 2018

The brain is one of the largest and most complex organs of the human body. The brain can be a vic... more The brain is one of the largest and most complex organs of the human body. The brain can be a victim of numerous pathologies, including malignant tumours, strokes, infection, head injuries, and diseases. Brain tumour extraction and analysis are challenging tasks for medical image processing due to the complexity of images. Since the growth of tumours causes asymmetry in the affected parts of the brain, the proposed method calculates asymmetry based on the intensity difference between the left and right of a Mid-Sagittal Plane (MSP). One of the problems of this method appears when the brain object is rotated or tilted. A new method is proposed to solve this problem, by locating the MidSagittal Plane in T1-weighted MRI images, based on the low intensity of InterHemispheric Fissure (IF) region. In this paper, we have proposed segmentation of the brain MRI image using K-means clustering algorithm followed by a connected component label to determine the location and size of a tumour. The...

Deep learning have gained lately popularity by achieving very good results for recognizing object... more Deep learning have gained lately popularity by achieving very good results for recognizing objects such as cars, plants, coffee cups in images. Big companies like Facebook, Google, Amazon are already using these methods to identify faces, recognize voice commands and even enable self-driving cars. Deep learning is based on classical neural networks and represents a method of machine learning and has evolved over the years to become a research field on its own. Deep neural networks are based on different models: Stacked Auto Encoder ,Deep Belief Networks, Deep Boltzmann Machine ,Convolutional Neural Networks, Recurrent Neural Networks. Most deep learning researchers are not programming neural networks directly but, they are using software libraries like: TensorFlow, Caffe2, Theano, Torch, etc. Deep learning is a central method for developing new applications in medical sector. Medical sector has access to vast quantities of patient data and images can be fed in the deep learning neur...

The brain is one of the largest and most complex organs of the human body. The brain can be a vic... more The brain is one of the largest and most complex organs of the human body. The brain can be a victim of numerous pathologies, including malignant tumours, strokes, infection, head injuries, and diseases. Brain tumour extraction and analysis are challenging tasks for medical image processing due to the complexity of images. Since the growth of tumours causes asymmetry in the affected parts of the brain, the proposed method calculates asymmetry based on the intensity difference between the left and right of a Mid-Sagittal Plane (MSP). One of the problems of this method appears when the brain object is rotated or tilted. A new method is proposed to solve this problem, by locating the MidSagittal Plane in T1-weighted MRI images, based on the low intensity of InterHemispheric Fissure (IF) region. In this paper, we have proposed segmentation of the brain MRI image using K-means clustering algorithm followed by a connected component label to determine the location and size of a tumour. The...

2018 22nd International Conference on System Theory, Control and Computing (ICSTCC)

2009 Second International Conference on Computer and Electrical Engineering, 2009

The protection of ownership and the protection of unauthorized tampering of multimedia data (audi... more The protection of ownership and the protection of unauthorized tampering of multimedia data (audio, image, video, and document) have become a major concern for the authors of multimedia. Image authentication verifies the originality of an image by detecting malicious manipulation. The protection of ownership and the protection of unauthorized tampering of multimedia data (audio, image, video, and document) have become a major concern for the authors of multimedia. Image authentication verifies the originality of an image by detecting malicious manipulations. Digital watermarking researches have generally focused on two classes of watermarks, fragile and robust. Fragile watermarks are used for authentication purposes and are capable of detecting even minute changes of the water marked images. Robust watermarks are designed to be detected even when attempts are made to remove them. In this paper, we focus on the first class of watermarking for digital images authentication by creating a mark based on the self similarities blocks properties of fractal encoding. We start with fractal encoding algorithm, then, partitioning the tested image into ranges and domains blocks, finding the pieces of ranges and their corresponding domains by minimizing the distances between them, finally, we create the mark by partitioning the same image into four columns of equal size and compute the mark through the determination of location for domain block parameters in which column number occurs.

Indian Journal of Science and Technology, 2018

Shape recognition is the most important issue in image understanding and computer vision. Shape r... more Shape recognition is the most important issue in image understanding and computer vision. Shape representation is a primary issue in shape recognition. The rotation angle of the object and the similarity between the horizontally/ vertically flipping shapes and the original shape