Papers by Mohammad Al-Azawi
Class C2 Images from MSRA 523 images
Class C4 Images from MSRA 117 images
Machine vision is still a challenging topic and attracts many researchers. One of the significant... more Machine vision is still a challenging topic and attracts many researchers. One of the significant differences between machine vision and human vision is attention whuch is one of the important properties of Human Vision System, with which the human can focus only on part of the scene at a time; scenes with more abrupt features shall attract human attention more than other regions. In this paper, we will simulate the human attention and discuss its application in machine vision and how it improves the result of the retrieval process and image identification and understanding. Artificial intelligence is used to give the algorithm the necessary intelligence to make it closer to human vision system. Its role is to identify and classify the salient points that are obtained from eye trackers or from saliency extraction algorithms.
Saliency Dataset Class C1 Images from MSRA 360 images
Saliency Dataset Class C3 Images from MSRA 117 images
2015 IEEE 8th GCC Conference & Exhibition, 2015
AbstractMachine vision is still a challenging topic and attracts researchers to carry out researc... more AbstractMachine vision is still a challenging topic and attracts researchers to carry out researches in this field. Efforts have been placed to design machine vision systems (MVS) that are inspired by human vision system (HVS). Attention is one of the important properties of HVS, with which the human can focus only on part of the scene at a time; regions with more abrupt features attract human attention more than other regions. This property improves the speed of HVS in recognizing and identifying the contents of a scene. In this paper, we will discuss the human attention and its application in MVS. In addition, a new method of extracting regions of interest and hence interesting objects from the images is presented. The new method utilizes neural networks as classifiers to classify important and unimportant regions.
Irregularity-based image regions saliency identification and evaluation
Saliency or salient region extraction from images is still a challenging field as it needs some u... more Saliency or salient region extraction from images is still a challenging field as it needs some understanding of the image and its nature. A technique that is suitable for some applications is not necessarily useful in other applications, thus, saliency identification is dependent upon the application. Based on a survey of existing methods of saliency detection, a new technique to extract the salient regions from an image is proposed that utilizes local features of the region surrounding each pixel. The level of saliency is decided based on the irregularity of the region with compared to other regions. To make the process fully automatic, a new Fuzzy-based thresholding technique has also been developed. In addition to the above, a survey of existing saliency evaluation techniques has been carried out and we have proposed new evaluation methods. The proposed saliency extraction technique has been compared with other algorithms reported in the literature, and the results are discussed in detail.
A New Edge Intersection-Based Salient Points Extraction and its Application in Computer Vision
In computer vision applications it is necessary to extract the regions of interest in order to re... more In computer vision applications it is necessary to extract the regions of interest in order to reduce the search space and to improve image contents identification. Human-Oriented Regions of Interest can be extracted by collecting some feedback from the user. The feedback usually provided by the user by giving different ranks for the identified regions in the image. This rank is then used to adapt the identification process. Nowadays eye tracking technology is widely used in different applications, one of the suggested applications is by using the data collected from the eye-tracking device, which represents the user gaze points in extracting the regions of interest. In this paper we shall introduce a new agglomerative clustering algorithm which uses blobs extraction technique and statistical measures in clustering the gaze points obtained from the eye tracker. The algorithm is fully automatic, which means does not need any human intervention to specify the stopping criterion. In the suggested algorithm the points are replaced with small regions (blobs) then these blobs are grouped together to form a cloud, from which the interesting regions are constructed.
International Journal of Computer Applications 83(9):36-40, December 2013. Published by Foundation of Computer Science, New York, USA, Dec 9, 2013
Image segmentation is one of the most important techniques in image processing. It is widely used... more Image segmentation is one of the most important techniques in image processing. It is widely used in different applications such as computer vision, digital pattern recognition, robot vision, etc. Histogram was the earliest feature that has been used for isolating objects from their background, it is widely applicable in different application in which one needs to divide the image into distinct regions like background and object. The thresholding technique is the most popular solution in which a value on the histogram is selected to separate the regions. This value, which is known as the threshold, should be specified in an appropriate way. One of the methods is by using the global minimum value of the histogram and divides the histogram into white and black (binary image). Due to the spatial and grey uncertainty and ambiguity, the extraction of the threshold value in a crispy way is not suitable always. To overcome such problems, the proposed method uses two membership functions to measure the whiteness and blackness of a member element. The pixel belonging to one of the region is dependent on the membership value it has according to the membership functions.
IRREGULARITY-BASED SALIENCY IDENTIFICATION AND EVALUATION
2013 IEEE International Conference on Computational Intelligence and Computing Research
Abstract – Saliency or Salient regions extractions form
images is still a challenging field sinc... more Abstract – Saliency or Salient regions extractions form
images is still a challenging field since it needs some
understanding for the image and the nature of the image.
The technique that is suitable in some application is not
necessarily useful in other application, thus, saliency
enhancement is application oriented. In this paper, a new
technique of extracting the salient regions from an image is
proposed which utilizes the local features of the surrounding
region of the pixels. The level of saliency is then decided
based on the global comparison of the saliency-enhanced
image. To make the process fully automatic a new Fuzzy-
Based thresholding technique has been proposed also. The
paper contains a survey of the state-of-the-art methods of
saliency evaluation and a new saliency evaluation technique
was proposed.
Keywords - Irregularity, Saliency, Image Processing,
Thresholding, fuzzy
sdiwc.net
Image recognition and understanding is one of the most interesting fields of researches. Its main... more Image recognition and understanding is one of the most interesting fields of researches. Its main idea is to bridge the gap between the high level human image understanding and the low level machine image representation. Quite a lot of applications have been suggested in different fields like medicine, industry, robotics, satellite imagery and other applications. This paper proposes a new approach of traffic signs image recognition and understanding using computational intelligent techniques and the application of this approach on intelligent cars which can recognize the traffic signs and take a decision according to the signs it reads. Supervised machine learning has been selected since the algorithm does not need to classify the images but to identify their precise meaning. Different neural networks have been trained and used in this paper. The best neural network has been selected, which uses genetic algorithms in its training, and is known as evolutionary training neural network. Different image features have also been investigated and discussed. the best of these features, which fit the requirement of the suggested algorithm, have been selected
Bimodal Histogram Based Image Segmentation Using Fuzzy-Logic
2012 National Conference on Artificial Intelligence Applications in Engineering, Jan 25, 2012
Image segmentation is one of the most important techniques in image processing, it is widely used... more Image segmentation is one of the most important techniques in image processing, it is widely used in variety of applications like; computer vision, digital pattern recognition, robot vision, etc. histogram was the earliest feature which has been used for segmenting objects from their background, it is widely applicable in different application in which one needs to divide the image into two distinct regions like background and object. The thresholding technique is the most popular solution in which a value on the histogram is selected to separate the two regions. This value which is called the threshold should be specified in an appropriate way. One of the methods is by using the global minimum value of the histogram and divides the histogram to white and black (binary image). Due to the spatial and gray uncertainty and ambiguity the image used to contain, crispy selection of the threshold value is not suitable always, to overcome such problem the proposed method uses two membership function to measure the whiteness and blackness of a member element. The pixel belonging to one of the region is dependent on the membership value it has according to the membership functions.
Automatic Stereo image matching using Line detection
International Archives of Photogrammetry and Remote Sensing, 1996
""An edge matching technique has been used in this work where an algorithm was developed for dete... more ""An edge matching technique has been used in this work where an algorithm was developed for detecting & coding the edge points which depends on the direction of the edge points the coding is followed by’ edge thinning, edge linking & isolated points removing .Then points tracing process is performed to form the straight lines. Lines matching operation is performed to group the lines in corresponding lines pairs .Features that are used in the matching process are ,line length ,line orientation ends point coordinates & line location.
""
Abstract: The effective use of “Information and Communication Technology (ICT)” is considered as ... more Abstract: The effective use of “Information and Communication Technology (ICT)” is considered as a keystone in the success of any organization. The applications of ICT vary from organization to organization. Higher Education has always been at the very fore-front in its dual role to invent as well as utilize the ICT for effective learning.
This paper focuses upon sharing the practitioners’ insights of the use of ICT inside a private college, Oman College of Management & Technology (OCMT), in Oman. The ICT used at OCMT include: Video-conferencing, Google Apps (Mail, Calendaring, and Document Sharing System), and supervised Online Exams. The insights would cover the use of the technology along with its challenges. In addition, the presented practitioners’ insights will be complemented with the students’ reflections.
This paper will discuss the use of (each) technology thoroughly; investigating, both the qualitative and quantitative data, of the use of ICT by the students, faculty and administrative staff. This paper is important because it accumulates the diversified viewpoints of an inter-disciplinary research team in the use of ICT for effective learning inside a learning environment.
A Traditional document is a written or printed paper that bears different kind of information abo... more A Traditional document is a written or printed paper that bears different kind of information about the organization activities e.g. legal, managerial, etc. Nowadays mainly there are two types of documents, which will be referred to as traditional (paper) documents and digital (electronic) documents. This discrimination between the types of documents in additional to the advances in the field of computer applications, networking, internet, and other digital processing tools were good motivations to use the Electronic - Archiving Systems (EAS). E-archiving is one of the first steps toward creating electronic environment on which e-government is based. There are a lot of risks and limitations of using traditional archiving systems which nowadays are not suitable to be used in organizations. This paper is a study of the archiving systems in both formats, traditional and electronic. The advantages and limitations of Electronic Archiving Systems (EAS) have been discussed briefly. A comparison between both electronic and traditional systems has been carried out as well. Traditional documents definition and digital (electronic) documents has been presented in additional to the methods of converting traditional (paper) documents into digital ones which is called the digitization process was discussed also. A brief description and the phases of constructing an e-archiving system has been proposed and discussed briefly. Finally, the cost feasibility of constructing an e-archive or converting a traditional archive into an electronic one has been studied in two aspects; long term coast and short term coast aspects.
Talks by Mohammad Al-Azawi
Teaching Documents by Mohammad Al-Azawi
Uploads
Papers by Mohammad Al-Azawi
images is still a challenging field since it needs some
understanding for the image and the nature of the image.
The technique that is suitable in some application is not
necessarily useful in other application, thus, saliency
enhancement is application oriented. In this paper, a new
technique of extracting the salient regions from an image is
proposed which utilizes the local features of the surrounding
region of the pixels. The level of saliency is then decided
based on the global comparison of the saliency-enhanced
image. To make the process fully automatic a new Fuzzy-
Based thresholding technique has been proposed also. The
paper contains a survey of the state-of-the-art methods of
saliency evaluation and a new saliency evaluation technique
was proposed.
Keywords - Irregularity, Saliency, Image Processing,
Thresholding, fuzzy
""
This paper focuses upon sharing the practitioners’ insights of the use of ICT inside a private college, Oman College of Management & Technology (OCMT), in Oman. The ICT used at OCMT include: Video-conferencing, Google Apps (Mail, Calendaring, and Document Sharing System), and supervised Online Exams. The insights would cover the use of the technology along with its challenges. In addition, the presented practitioners’ insights will be complemented with the students’ reflections.
This paper will discuss the use of (each) technology thoroughly; investigating, both the qualitative and quantitative data, of the use of ICT by the students, faculty and administrative staff. This paper is important because it accumulates the diversified viewpoints of an inter-disciplinary research team in the use of ICT for effective learning inside a learning environment.
Talks by Mohammad Al-Azawi
Teaching Documents by Mohammad Al-Azawi