Papers by Nijad Al-Najdawi
Using Geographic Information Systems (GIS) in Za'atari refugee camp, Jordan for refugee community information management and mobilization: The RefuGIS project
2017 IEEE Global Humanitarian Technology Conference (GHTC), 2017
The inherent geographic nature of displacement in refugee camps is requiring further use of Geogr... more The inherent geographic nature of displacement in refugee camps is requiring further use of Geographic Information Systems (GIS) technology for community-based information and asset management. Additionally, refugees have a fundamental need for livelihood development in host countries due to the protracted nature of displacement. This paper presents our work on the Refugee GIS or ‘RefuGIS’ project that addresses these two topics via a training and capacity building education program and community mobilization efforts. RefuGIS is currently at the prototype level of development in the Za'atari Syrian Refugee Camp in northern Jordan. RefuGIS is the one of world's first efforts at enabling GIS capacity among refugees themselves and was funded by a grant from the United Nations High Commissioner for Refugees (UNHCR) Innovation fund. Specifically, this paper will discuss (a) design of the RefuGIS educational program via utilization of a non-profit GIS software donation, hardware procurement and customized GIS educational curriculum, (b) selection of refugee participants through spatial thinking aptitude testing, (c) practical experiences and lessons learned from education, training, and capacity building of refugees on the topics of GIS and related information technology skills, (d) insights into use of GIS as a community information and asset management tool by refugees themselves as demonstrated by evaluation of project outputs such as reference mapping products and field surveys conducted by refugees. Lessons learned from the RefuGIS project, even at the prototype stage, have potential to inform other refugee community information and asset management projects. Since creation of the project, refugees in Za'atari camp have been able to obtain cash-for-work GIS jobs in Za'atari using the skills learned via the RefuGIS project. The RefuGIS project demonstrates the refugee livelihood potential that training and capacity building around GIS can build as well as the empowerment effect that technology education and livelihood development can bring to refugees.
Jordanian Journal of Computers and Information Technology, 2018
Although the advancements in hardware solutions are growing exponentially along with the communic... more Although the advancements in hardware solutions are growing exponentially along with the communication channels capacity, high quality video encoders for real-time applications are still considered an open area of research. The majority of researchers interested in video encoders target their investigations towards motion estimation and block matching algorithms. Many algorithms that aim to reduce the total number of required mathematical operations when compared to Full Search have been proposed. However, the results often converge to local minima and a significant amount of computations is still required. Therefore, in this research, a hierarchy-based block matching method that facilitates the transmission of high bit-rate videos over standard communication methods is proposed. The proposed algorithm is based on the frequency domain, where the algorithm examines the similarities between a chosen frequency subset, which significantly reduces the total number of comparisons and the total mathematical computations required per block.
Cast shadow modelling and detection
Computer vision applications are often confronted by the need to differentiate between objects an... more Computer vision applications are often confronted by the need to differentiate between objects and their shadows. A number of shadow detection algorithms have been proposed in literature, based on physical, geometrical, and other heuristic techniques. While most of these existing approaches are dependent on the scene environments and object types, the ones that are not, are classified as superior to others conceptually and in terms of accuracy. Despite these efforts, the design of a generic, accurate, simple, and efficient shadow detection algorithm still remains an open problem. In this thesis, based on a physically-derived hypothesis for shadow identification, novel, multi-domain shadow detection algorithms are proposed and tested in the spatial and transform domains. A novel "Affine Shadow Test Hypothesis" has been proposed, derived, and validated across multiple environments. Based on that, several new shadow detection algorithms have been proposed and modelled for short-duration video sequences, where a background frame is available as a reliable reference, and for long duration video sequences, where the use of a dedicated background frame is unreliable. Finally, additional algorithms have been proposed to detect shadows in still images, where the use of a separate background frame is not possible. In this approach, the author shows that the proposed algorithms are capable of detecting cast, and self shadows simultaneously. All proposed algorithms have been modelled, and tested to detect shadows in the spatial (pixel) and transform (frequency) domains and are compared against state-of-art approaches, using popular test and novel videos, covering a wide range of test conditions. It is shown that the proposed algorithms outperform most existing methods and effectively detect different types of shadows under various lighting and environmental conditions.
International Journal of Advanced Computer Science and Applications, 2016
Numerous fast-search block motion estimation algorithms have been developed to circumvent the hig... more Numerous fast-search block motion estimation algorithms have been developed to circumvent the high computational cost required by the full-search algorithm. These techniques however often converge to a local minimum, which makes them subject to noise and matching errors. Hence, many spatial domain block matching algorithms have been developed in literature. These algorithms exploit the high correlation that exists between pixels inside each frame block. However, with the block transformed frequencies, block matching can be used to test the similarities between a subset of selected frequencies that correctly identify each block uniquely; therefore fewer comparisons are performed resulting in a considerable reduction in complexity. In this work, a two-level hierarchical fast search motion estimation algorithm is proposed in the frequency domain. This algorithm incorporates a novel search pattern at the top level of the hierarchy. The proposed hierarchical method for motion estimation not only produces consistent motion vectors within each large object, but also accurately estimates the motion of small objects with a substantial reduction in complexity when compared to other benchmark algorithms.
A survey of cast shadow detection algorithms
Pattern Recognition Letters, 2012
ABSTRACT Cast shadows need careful consideration in the development of robust dynamic scene analy... more ABSTRACT Cast shadows need careful consideration in the development of robust dynamic scene analysis systems. Cast shadow detection is critical for accurate object detection in video streams, and their misclassification can cause errors in segmentation and tracking. Many algorithms for shadow detection have been proposed in the literature; however a complete, comparative evaluation of existing approaches is lacking. This paper presents a comprehensive survey of shadow detection methods, organised in a novel taxonomy based on object/environment dependency and implementation domain. In addition a comparative evaluation of representative algorithms, based on quantitative and qualitative metrics is presented to evaluate the algorithms on a benchmark suite of indoor and outdoor video sequences.
A concealed ammo detection system for passengers luggage screening
2014 International Conference on Multimedia Computing and Systems (ICMCS), 2014
Airport passenger screening programs mainly involve checkpoint screening using magnetometers to d... more Airport passenger screening programs mainly involve checkpoint screening using magnetometers to detect metallic weapons on passengers and X-Ray systems to examine carry-on items. The aviation security system is a human system involving extensive reliance on not only the human's perception but also the human's performance, decision making, and judgment. This is particularly true with X-Ray screening systems as they involve human resource intensive activities in order to detect and resolve potential threat items. In addition to the screener's performance which remains a continuing concern, the screening personnel and for many reasons, have long been regarded as a highly fallible and vulnerable element of the aviation screen. Adversaries seeking to carry out unethical measures by carrying explosive devices, bomb making components, ammos, or handheld weapons through screening checkpoints may attempt to exploit various limitations in not only the human's perception and performance but also in the limitations of the current technology capabilities that may compromise security. Although not all security systems are the same, one security hole in airport X-Ray security systems is that they fail to detect all types of ammos known to the industry. In this research, the authors specifically target AK-47 machinegun bullets, 9mm handgun bullets, and 12 gauge shotgun shells, and propose a system that employs digital image processing techniques in order to detect such type of bullets and shells. The proposed system will also assist the security staff by automatically notifying them for any possibility that such a bullet might be carried in a passenger's carry-on item. For testing purposes, the author built a dataset comprising 150 X-Ray images of passenger's luggage that contain different types of bullets and shotgun shells. Simple image processing techniques that includes image enhancement, conversion, labeling of connected components and geometric distance calculations were applied to help in the detection process.
Image cryptographic algorithm based on the Haar wavelet transform
Information Sciences, 2014
ABSTRACT Lossless encryption methods are more applicable than lossy encryption methods when margi... more ABSTRACT Lossless encryption methods are more applicable than lossy encryption methods when marginal distortion is not tolerable. In this research, the authors propose a novel lossless symmetric key encryption/decryption technique. In the proposed algorithm, the image is transformed into the frequency domain using the Haar wavelet transform, then the image sub-bands are encrypted in a such way that guarantees a secure, reliable, and an unbreakable form. The encryption involves scattering the distinguishable frequency data in the image using a reversible weighting factor amongst the rest of the frequencies. The algorithm is designed to shuffle and reverse the sign of each frequency in the transformed image before the image frequencies are transformed back to the pixel domain. The results show a total deviation in pixel values between the original and encrypted image. The decryption algorithm reverses the encryption process and restores the image to its original form. The proposed algorithm is evaluated using standard security and statistical methods; results show that the proposed work is resistant to most known attacks and more secure than other algorithms in the cryptography domain.
IET Computer Vision, 2012
Many fast search motion estimation algorithms have been developed to reduce the computational cos... more Many fast search motion estimation algorithms have been developed to reduce the computational cost required by fullsearch algorithms. Fast search motion estimation techniques often converge to a local minimum, providing a significant reduction in computational cost. The motion vector measurement process in fast search algorithms is subject to noise and matching errors. Therefore researchers have investigated the use of Kalman filtering in order to seek optimal estimates. In this work, the authors propose a new fast stochastic motion estimation technique that requires 5% of the total computations required by the full-search algorithm, and results in a quality that outperforms most of the well-known fast searching algorithms. The measured motion vectors are obtained using a simplified hierarchical search block-matching algorithm, and are used as the measurement part of the Kalman filter. As for the prediction part of the filter, it is assumed that the motion vector of a current block can be predicted from its four neighbouring blocks. Using the predicted and measured motion vectors, the best estimates for motion vectors are obtained. Using standard methods of accuracy measurements, results show that the performance of the proposed technique approaches that of the full-search algorithm.
Mammogram Enhancement and Segmentation Methods: Classification, Analysis, and Evaluation
ABSTRACT Breast cancer is the leading cause of deaths among female cancer patients. Mammography i... more ABSTRACT Breast cancer is the leading cause of deaths among female cancer patients. Mammography is the most effective technique for breast cancer screening and detection of abnormalities. However, early detection of breast cancer is dependent on both the radiologist’s ability to read mammograms and the quality of mammogram images. The aim of this paper is to conduct a comprehensive survey of existing mammogram enhancement and segmentation techniques. Each method is classified, analyzed, and compared against other approaches. To examine the accuracy of the mammogram enhancement and segmentation techniques, the sensitivity and specificity of the approaches is presented and compared where applicable. Finally, this research provides taxonomy for the available approaches and highlights the best available enhancement and segmentation methods.
Neural Computing and Applications
Digital image processing techniques and algorithms have become a great tool to support medical ex... more Digital image processing techniques and algorithms have become a great tool to support medical experts in identifying, studying, diagnosing certain diseases. Image segmentation methods are of the most widely used techniques in this area simplifying image representation and analysis. During the last few decades, many approaches have been proposed for image segmentation, among which multilevel thresholding methods have shown better results than most other methods. Traditional statistical approaches such as the Otsu and the Kapur methods are the standard benchmark algorithms for automatic image thresholding. Such algorithms provide optimal results, yet they suffer from high computational costs when multilevel thresholding is required, which is considered as an optimization matter. In this work, the Harris hawks optimization technique is combined with Otsu's method to effectively reduce the required computational cost while maintaining optimal outcomes. The proposed approach is tested on a publicly available imaging datasets, including chest images with clinical and genomic correlates, and represents a rural COVID-19-positive (COVID-19-AR) population. According to various performance measures, the proposed approach can achieve a substantial decrease in the computational cost and the time to converge while maintaining a level of quality highly competitive with the Otsu method for the same threshold values. Keywords Harris hawks optimization Á Multilevel thresholding Á Image segmentation Á Otsu method Á Covid-19 Á CT images
Lossless image cryptography algorithm based on discrete cosine transform
Int. Arab J. Inf. Technol., 2012
T he science of cryptography has recently attracted significant attention, as progressively more ... more T he science of cryptography has recently attracted significant attention, as progressively more information is stored and transmitted in electronic form. Cryptography is the discipline of using codes to encrypt data into an unreadable format that only the targeted recipients can decrypt and read. Encryption methods can be divided into two categories: lossy and lossless. In lossy encryption methods, the decrypted image details are vulnerable to distortion. Lossless encryption methods are more relevant when marginal distortion is not tolerable. In this research, the authors propose a novel lossless encryption/decryption technique. In the proposed algorithm, the image is transformed into the frequency domain, where low and high frequencies are processed in a way that guarantees a secure, reliable, and an unbreakable form. The encryption algorithm uses the discrete cosine transform to convert the target image into the frequency domain, after which the encryption involves scattering the...
An automated real-time people tracking system based on KLT features detection
Int. Arab J. Inf. Technol., 2012
The advancement of technology allows video acquisition devices to have a better performance, ther... more The advancement of technology allows video acquisition devices to have a better performance, thereby increasing the number of applications that can effectively utilize digital video. Compared to still images, video sequences provide more information about how objects and scenarios change over time. Tracking humans is of interest for a variety of applications including surveillance, activity monitoring and gate analysis. Many efficient object tracking algorithms have been proposed in literature, however part of those algorithms are semi-automatic requiring human interference. As for the fully automated algorithms, most of them are not applicable to real-time applications. This paper presents a low cost automatic object tracking algorithm suitable for use in real-time video based systems. The novelty of the proposed system is that it uses a simplified version of the Kanade-Lucas-Tomasi (KLT) technique to detect features of both continuous and discontinuous nature. As discontinuous fea...
J. Univers. Comput. Sci., 2016
Algebraic-Geometric (AG) codes are new paradigm in coding theory with promising performance impro... more Algebraic-Geometric (AG) codes are new paradigm in coding theory with promising performance improvements and diverse applications in point to point communications services and system security. AG codes offer several advantages over stateof-the art Reed-Solomon (RS) codes. Algebraic-Geometric Codes are proposed and implemented in this paper. The design, construction and implementation are investigated and a software platform has been developed. Simulation results are presented for the first time showing significant performance improvements of AG codes over RS codes using different modulation schemes. The superiority in error correcting and security of AG codes over RS codes has been demonstrated clearly when Rayleigh fading channel is used. Also the results show an obvious improvement when using higher modulation schemes, namely 16QAM and 64QAM.
An adaptive approach for real-time road traffic congestion detection using adaptive background extraction
Traffic congestion is a situation on road networks that occurs as road use increases. When traffi... more Traffic congestion is a situation on road networks that occurs as road use increases. When traffic demand increase, the interaction between vehicles slows the speed of the traffic stream and congestion occurs. As demand approaches the capacity of a road, extreme traffic congestion sets in. Current techniques for road,traffic monitoring rely on sensors which have limited capabilities, inflexibility, and are often costly and disruptive to install. The use of video cameras coupled with computer vision techniques offers an attractive alternative to the current sensors. Vision based sensors have the potential to measure a far greater variety of traffic parameters compared to conventional sensors. This work presents an approach for traffic congestion detection based an adaptive background extraction and edge detection techniques using rang filtering. The proposed work uses a special shadow detection algorithm that reduces the chances of misclassification and enhances the segmentation proc...
Infrastructure Evolution Analysis via Remote Sensing in an Urban Refugee Camp – Evidence from Za’atari
Procedia Engineering, 2016
Abstract In this paper, we present a preliminary analysis of infrastructure change in an urban re... more Abstract In this paper, we present a preliminary analysis of infrastructure change in an urban refugee camp. Specifically, we used visible remote satellite imagery from the Za’atari Syrian refugee camp in Jordan to begin to understand how the camp's infrastructure has evolved and changed over time. Our analysis and interpretation of imagery was validated with contextual feedback provided by a refugee living in the camp. We demonstrate how refugees will modify the infrastructure in terms of moving caravan structures closer to important resources such as food and other small markets. We also demonstrate how resources initially given to refugees such as tents become re-used over time for different purposes. The paper concludes with ideas for future remote sensing research of refugee camps and how such research could tie into camp management practice.
Mammogram image visual enhancement, mass segmentation and classification
Applied Soft Computing, 2015
Reveal the optimal combination of various enhancement methods.Segment breast region in order to o... more Reveal the optimal combination of various enhancement methods.Segment breast region in order to obtain better visual interpretation.To assist radiologists in making accurate decisions, analysis and classifications.Tumor classification accuracy and sensitivity values of 81.1% and 86%, respectively.Participated radiologists are pleased with the results and acknowledged the work. Mammography is the most effective technique for breast cancer screening and detection of abnormalities. However, early detection of breast cancer is dependent on both the radiologist's ability to read mammograms and the quality of mammogram images. In this paper, the researchers have investigated combining several image enhancement algorithms to enhance the performance of breast-region segmentation. The masses that appear in mammogram images are further analyzed and classified into four categories that include: benign, probable benign and possible malignant, probable malignant and possible benign, and malignant. The main contribution of this work is to reveal the optimal combination of various enhancement methods and to segment breast region in order to obtain better visual interpretation, analysis, and classification of mammogram masses to assist radiologists in making more accurate decisions. The experimental dataset consists of a total of more than 1300 mammogram images from both the King Hussein Cancer Center and Jordan Hospital. Results achieved tumor classification accuracy values of 90.7%. Moreover, the results showed a sensitivity of 96.2% and a specificity of 94.4% for the mass classifying algorithm. Radiologists from both institutes have acknowledged the results and confirmed that this work has lead to better visual quality images and that the segmentation and classification of tumors has aided the radiologists in making their diagnoses.
International Arab Journal of Information Technology
The principle objective of image enhancement is to process an image so that the result is more su... more The principle objective of image enhancement is to process an image so that the result is more suitable than the original image for a specific application. This paper presents a novel hybrid method for enhancing digital X-Ray radiograph images by seeking optimal spatial and frequency domain image enhancement combinations. The selected methods from the spatial domain include: negative transform, histogram equalization and power-law transform. Selected enhancement methods from the frequency domain include: gaussian low and high pass filters and butterworth low and high pass filters. Over 80 possible combinations have been tested, where some of the combinations have yielded in an optimal enhancement compared to the original image, according to radiologist subjective assessments. Medically, the proposed methods have clarified the vascular impression in hilar regions in regular X-ray images. This can help radiologists in diagnosing vascular pathology, such as pulmonary embolism in case o...
International Journal of Computer Applications, 2014
Object detection, tracking and recognition in real time is a very essential task in computer visi... more Object detection, tracking and recognition in real time is a very essential task in computer vision. There are lots of research work have been done in this area. Yet it needs to be accuracy in recognizing object. The most objective of this review is to present an overview of the approaches used and also the challenges involved. In this paper we concentrate on different object detection methods, tracking and recognition methods are discussed.
Motion estimation algorithms have proven to be effective in the reduction of video bit-rates whil... more Motion estimation algorithms have proven to be effective in the reduction of video bit-rates while preserving the good quality. The most popular technique for motion estimation is block matching. Block matching algorithms involve searching techniques for block movements between consecutive video frames. Researchers try to develop fast search motion estimation algorithms to reduce the computational cost required by full-search algorithms. In this research, the author presents a new fast search algorithm based on the hierarchical search approach. The original image is sub-sampled into additional two levels. The full search is performed on the highest level where the complexity is relatively low. The enhanced Three-Step Search algorithm and a new proposed searching algorithm are used in the consecutive two levels. The results show that, the performance of the proposed hierarchal search algorithm is close to the full search with 16.6% complexity and a high matching quality.
Web-based visualization-Accessibility and Usability
ABSTRACT Early in the 1990s, web accessibility information was available from organizations such ... more ABSTRACT Early in the 1990s, web accessibility information was available from organizations such as the Trace Research and Development Centre and companies such as IBM. The City of San Jose Web Page Disability Access Design Standard was developed in 1996, and the AUS Standards for Accessible Web Design were available online in 1997. Also in 1997, the WWW Consortium established the Web Accessibility Initiative (WAI) [2] and in 1999 the Web Content Accessibility Guidelines (WCAG) 1.0 were finalized as a Recommendation. The majority of website designers and developers were, in the recent past, not aware of accessibility issues. Awareness gradually increased with media articles on accessibility, in media, designer and developer websites, and also as accessibility began to appear in conference topics. While more people began to hear about accessibility, the majority of websites still did little to implement it. There are several reasons why so many websites were not accessible, besides lack of awareness, most designers, and developers, did not understand the benefits of providing accessible websites and so were not convinced that it was important for their business. Even those who did want to incorporate accessibility, had difficulties finding the resources. However, recent legal and regulatory activity changed that. Usability is developed to provide principles for usable interface and interaction development within Company's NAME Products. To maintain position in an increasingly difficult market, the software that is easiest to use has the competitive advantage. Sales support staff report that NAME Products customers are shouting for products that are user-friendly, consistent and functional.
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Papers by Nijad Al-Najdawi