Amer Dawoud - Academia.edu (original) (raw)
Papers by Amer Dawoud
The present work focuses on developing miniaturized, light weight electrochemical sensors for det... more The present work focuses on developing miniaturized, light weight electrochemical sensors for detection of chemical warfare agents (CWAs) like sarin and tabun simulants, i.e., diisopropyl fluorophosphate (DFP), and O,S-diethyl methyl phosphonothioate (O,S-DEMPT). Differential pulse voltammetry (DPV) was employed to examine the redox properties of capturing molecular probe CE2 with the nerve agent stimulants. Coupling of a portable potentiostat with the drone technology could allow on-situ and remote detection of analytes such CWAs to be realized, which can be crucially important to the national and global securities.
Proceedings of SPIE, Apr 12, 2004
In this paper, we propose a novel decision fusion algorithm for target tracking in forward lookin... more In this paper, we propose a novel decision fusion algorithm for target tracking in forward looking infrared (FLIR) image sequences recorded from an airborne platform. The algorithm allows the fusion of complementary ego-motion compensation and tracking algorithms. We identified three modes that contribute to the failure of the tracking system: (1) the sensor ego-motion failure mode, which causes the movement of the target more than the operational limits of the tracking stage; (2) the tracking failure mode, which occurs when the tracking algorithm fails to determine the correct location of the target in the new frame; (3) the distortion of the reference image failure mode, which happens when the reference image accumulates walk-off error, specially when the target is changing in size, shape or orientation from frame to frame. The proposed algorithm prevents these failure modes from developing unrecoverable tracking failures. The overall performance of the algorithm is guaranteed to be much better than any individual tracking algorithm used in the fusion. The experiments performed on the AMCOM FLIR data set verify the robustness of the algorithm.
2021 3rd IEEE Middle East and North Africa COMMunications Conference (MENACOMM)
Drones are becoming more influential and inter-connected in today’s world. Internet of drones (Io... more Drones are becoming more influential and inter-connected in today’s world. Internet of drones (IoD) is an architecture created over an area in which drones can be controlled and accessed by users through the internet. The main problem with IoD is that users want to access real-time data (routes, locations, surveillance video, etc.) on drones within an area. Drones’ authentication is one of the primary security services that should be lightweight to enable real-time access to the data submitted by legitimate drones. We propose a privacy-aware and hardware accelerated-based authentication scheme using the k-nearest neighbor (kNN) encryption algorithm. In addition, we use the hardware acceleration techniques within the Field Programmable Gate Arrays (FPGAs) to perform the kNN encryption and user authentication as a hardware component. This allows authorized users to obtain information only from authenticated drones within the IoD environment. Our performance analysis shows that our scheme outperforms similar schemes quickly and efficiently while performing much larger computational tasks through the FPGA parallel process.
International journal of imaging and robotics, 2015
This paper proposes a novel thresholding-based approach for the segmentation of pigmented skin le... more This paper proposes a novel thresholding-based approach for the segmentation of pigmented skin lesion images regarding malignant melanoma diagnosis. This problem is challenging because of the high uncertainty and fuzziness encountered at the border between the lesion and the skin. The main contribution of this paper is the improvement of the segmentation accuracy of binarization algorithm that relies only on histogram information by integrating the spatial information. The proposed algorithm fuses Type-2 fuzziness measure in Graph Cuts (GC) energy minimization process, and by integrating the spatial information (pixel positions), embedded in GC energy minimization, the proposed method performs better than methods that relay only on the histogram information. Experimental results performed on dermoscopic images demonstrate the effectiveness of the algorithm in comparison with other algorithms.
2021 IEEE International Systems Conference (SysCon), 2021
Large number of physical systems such as electric vehicles and energy storage elements are connec... more Large number of physical systems such as electric vehicles and energy storage elements are connected to the main grid. Monitoring and regulating of this interconnected cyberphysical power system state within a short period of time is a challenging task, and it can perform by the process of grid state estimation. This paper proposes a multi-agent based optimal distributed dynamic state estimation algorithm for smart grid incorporating intermittent electric vehicles and turbines. After mathematically representation of large-scale grid systems into a compact state-space framework, the smart sensors are installed to get real-time measurements which are manipulated by environmental noise. A distributed smart grid state estimation process is developed and verified. Each agent learns and runs an innovation and consensus type distributed scheme based on local measurements, previous and neighbouring estimated grid states. In this way, each local agent estimated grid state converges to the global consensus estimation over time. The proposed algorithm can effectively reconstruct the original grid states.
NAECON 2018 - IEEE National Aerospace and Electronics Conference
Information
Silicon Physical Unclonable Functions (sPUFs) are one of the security primitives and state-of-the... more Silicon Physical Unclonable Functions (sPUFs) are one of the security primitives and state-of-the-art topics in hardware-oriented security and trust research. This paper presents an efficient and dynamic ring oscillator PUFs (d-ROPUFs) technique to improve sPUFs security against modeling attacks. In addition to enhancing the Entropy of weak ROPUF design, experimental results show that the proposed d-ROPUF technique allows the generation of larger and updated challenge-response pairs (CRP space) compared with simple ROPUF. Additionally, an innovative hardware-oriented security algorithm, namely, the Optimal Time Delay Algorithm (OTDA), is proposed. It is demonstrated that the OTDA algorithm significantly improves PUF reliability under varying operating conditions. Further, it is shown that the OTDA further efficiently enhances the d-ROPUF capability to generate a considerably large set of reliable secret keys to protect the PUF structure from new cyber-attacks, including machine lear...
Lecture Notes in Computer Science, 2010
IET Computer Vision, 2011
IEEE Transactions on Image Processing, 2000
In this paper, we present a new class of iterative regularization methods in the setting of Besov... more In this paper, we present a new class of iterative regularization methods in the setting of Besov spaces, which can be seen as generalizations of J. Xu's method. By incorporating translation invariant wavelet transform, minimizers of the new methods can be understood as the alternative to translation invariant wavelet shrinkage with weight that is dependent on the wavelet decomposition scale and the Besov smooth order. And we generalize the iterative regularization methods to a new class of nonlinear inverse scale spaces with scale and Besov smooth order dependent weight. The numerical results show an excellent denoising effect and improvement over J. Xu's method.
low level medium high level level probability *** match filter back prop.
Proceedings 2003 International Conference on Image Processing, Oct 14, 2003
Existing binarization methods are categorized as either global or local. In this paper we present... more Existing binarization methods are categorized as either global or local. In this paper we present a new category, where the image is considered as a collection of sub-images. Each sub-image provides a statistical model for the handwritten characters that will be used to optimize the binarization of other sub-images. This method can be applied to different types of documents and
Iet Computer Vision, 2013
Ieee Transactions on Image Processing a Publication of the Ieee Signal Processing Society, Feb 1, 2007
In this paper, we generalize the iterative regularization method and the inverse scale space meth... more In this paper, we generalize the iterative regularization method and the inverse scale space method, recently developed for total-variation (TV) based image restoration, to wavelet-based image restoration. This continues our earlier joint work with others where we applied these techniques to variational-based image restoration, obtaining significant improvement over the Rudin-Osher-Fatemi TV-based restoration. Here, we apply these techniques to soft shrinkage and obtain the somewhat surprising result that a) the iterative procedure applied to soft shrinkage gives firm shrinkage and converges to hard shrinkage and b) that these procedures enhance the noise-removal capability both theoretically, in the sense of generalized Bregman distance, and for some examples, experimentally, in terms of the signal-to-noise ratio, leaving less signal in the residual.
Lecture Notes in Computer Science, 2010
This paper proposes an algorithm that fuses edge information into Markov Random Fields (MRF) regi... more This paper proposes an algorithm that fuses edge information into Markov Random Fields (MRF) region growing based image segmentation. The idea is to segment the image in a way that takes edge information into consideration. This is achieved by modifying the energy function minimization process so that it would penalize merging regions that have real edges in the boundary between them. Experimental results confirming the hypothesis that the addition of edge information increases the precision of the segmentation by ensuring the conservation of the objects contours during the region growing.
Binarization of document images with poor contrast, strong noise, complex patterns, and variable ... more Binarization of document images with poor contrast, strong noise, complex patterns, and variable modalities in the gray-scale histograms is a challenging problem. A new binarization algorithm has been developed to address this problem for personal cheque images. The main contribution of this approach is optimizing the binarization of a part of the document image that suffers from noise interference, referred to as the Target Sub-Image (TSI), using information easily extracted from another noise-free part of the same image, referred to as the Model Sub-Image (MSI). Simple spatial features extracted from MSI are used as a model for handwriting strokes. This model captures the underlying characteristics of the writing strokes, and is invariant to the handwriting style or content. This model is then utilized to guide the binarization in the TSI. Another contribution is a new technique for the structural analysis of document images, which we call "Wavelet Partial Reconstruction" (WPR). The algorithm was tested on 4,200 cheque images and the results show significant improvement in binarization quality in comparison with other well-established algorithms.
Proceedings of Sixth International Conference on Document Analysis and Recognition, 2001
Binarization of document images with poor contrast, strong noise complex patterns and variable mo... more Binarization of document images with poor contrast, strong noise complex patterns and variable modalities in the gray-scale histograms is a challenging problem. We present a binarization algorithm based on an image dependent model to address this problem for a cheque processing application. The proposed algorithm seeks an optimal threshold that would eliminate the background noise, while preserving as much character
The present work focuses on developing miniaturized, light weight electrochemical sensors for det... more The present work focuses on developing miniaturized, light weight electrochemical sensors for detection of chemical warfare agents (CWAs) like sarin and tabun simulants, i.e., diisopropyl fluorophosphate (DFP), and O,S-diethyl methyl phosphonothioate (O,S-DEMPT). Differential pulse voltammetry (DPV) was employed to examine the redox properties of capturing molecular probe CE2 with the nerve agent stimulants. Coupling of a portable potentiostat with the drone technology could allow on-situ and remote detection of analytes such CWAs to be realized, which can be crucially important to the national and global securities.
Proceedings of SPIE, Apr 12, 2004
In this paper, we propose a novel decision fusion algorithm for target tracking in forward lookin... more In this paper, we propose a novel decision fusion algorithm for target tracking in forward looking infrared (FLIR) image sequences recorded from an airborne platform. The algorithm allows the fusion of complementary ego-motion compensation and tracking algorithms. We identified three modes that contribute to the failure of the tracking system: (1) the sensor ego-motion failure mode, which causes the movement of the target more than the operational limits of the tracking stage; (2) the tracking failure mode, which occurs when the tracking algorithm fails to determine the correct location of the target in the new frame; (3) the distortion of the reference image failure mode, which happens when the reference image accumulates walk-off error, specially when the target is changing in size, shape or orientation from frame to frame. The proposed algorithm prevents these failure modes from developing unrecoverable tracking failures. The overall performance of the algorithm is guaranteed to be much better than any individual tracking algorithm used in the fusion. The experiments performed on the AMCOM FLIR data set verify the robustness of the algorithm.
2021 3rd IEEE Middle East and North Africa COMMunications Conference (MENACOMM)
Drones are becoming more influential and inter-connected in today’s world. Internet of drones (Io... more Drones are becoming more influential and inter-connected in today’s world. Internet of drones (IoD) is an architecture created over an area in which drones can be controlled and accessed by users through the internet. The main problem with IoD is that users want to access real-time data (routes, locations, surveillance video, etc.) on drones within an area. Drones’ authentication is one of the primary security services that should be lightweight to enable real-time access to the data submitted by legitimate drones. We propose a privacy-aware and hardware accelerated-based authentication scheme using the k-nearest neighbor (kNN) encryption algorithm. In addition, we use the hardware acceleration techniques within the Field Programmable Gate Arrays (FPGAs) to perform the kNN encryption and user authentication as a hardware component. This allows authorized users to obtain information only from authenticated drones within the IoD environment. Our performance analysis shows that our scheme outperforms similar schemes quickly and efficiently while performing much larger computational tasks through the FPGA parallel process.
International journal of imaging and robotics, 2015
This paper proposes a novel thresholding-based approach for the segmentation of pigmented skin le... more This paper proposes a novel thresholding-based approach for the segmentation of pigmented skin lesion images regarding malignant melanoma diagnosis. This problem is challenging because of the high uncertainty and fuzziness encountered at the border between the lesion and the skin. The main contribution of this paper is the improvement of the segmentation accuracy of binarization algorithm that relies only on histogram information by integrating the spatial information. The proposed algorithm fuses Type-2 fuzziness measure in Graph Cuts (GC) energy minimization process, and by integrating the spatial information (pixel positions), embedded in GC energy minimization, the proposed method performs better than methods that relay only on the histogram information. Experimental results performed on dermoscopic images demonstrate the effectiveness of the algorithm in comparison with other algorithms.
2021 IEEE International Systems Conference (SysCon), 2021
Large number of physical systems such as electric vehicles and energy storage elements are connec... more Large number of physical systems such as electric vehicles and energy storage elements are connected to the main grid. Monitoring and regulating of this interconnected cyberphysical power system state within a short period of time is a challenging task, and it can perform by the process of grid state estimation. This paper proposes a multi-agent based optimal distributed dynamic state estimation algorithm for smart grid incorporating intermittent electric vehicles and turbines. After mathematically representation of large-scale grid systems into a compact state-space framework, the smart sensors are installed to get real-time measurements which are manipulated by environmental noise. A distributed smart grid state estimation process is developed and verified. Each agent learns and runs an innovation and consensus type distributed scheme based on local measurements, previous and neighbouring estimated grid states. In this way, each local agent estimated grid state converges to the global consensus estimation over time. The proposed algorithm can effectively reconstruct the original grid states.
NAECON 2018 - IEEE National Aerospace and Electronics Conference
Information
Silicon Physical Unclonable Functions (sPUFs) are one of the security primitives and state-of-the... more Silicon Physical Unclonable Functions (sPUFs) are one of the security primitives and state-of-the-art topics in hardware-oriented security and trust research. This paper presents an efficient and dynamic ring oscillator PUFs (d-ROPUFs) technique to improve sPUFs security against modeling attacks. In addition to enhancing the Entropy of weak ROPUF design, experimental results show that the proposed d-ROPUF technique allows the generation of larger and updated challenge-response pairs (CRP space) compared with simple ROPUF. Additionally, an innovative hardware-oriented security algorithm, namely, the Optimal Time Delay Algorithm (OTDA), is proposed. It is demonstrated that the OTDA algorithm significantly improves PUF reliability under varying operating conditions. Further, it is shown that the OTDA further efficiently enhances the d-ROPUF capability to generate a considerably large set of reliable secret keys to protect the PUF structure from new cyber-attacks, including machine lear...
Lecture Notes in Computer Science, 2010
IET Computer Vision, 2011
IEEE Transactions on Image Processing, 2000
In this paper, we present a new class of iterative regularization methods in the setting of Besov... more In this paper, we present a new class of iterative regularization methods in the setting of Besov spaces, which can be seen as generalizations of J. Xu's method. By incorporating translation invariant wavelet transform, minimizers of the new methods can be understood as the alternative to translation invariant wavelet shrinkage with weight that is dependent on the wavelet decomposition scale and the Besov smooth order. And we generalize the iterative regularization methods to a new class of nonlinear inverse scale spaces with scale and Besov smooth order dependent weight. The numerical results show an excellent denoising effect and improvement over J. Xu's method.
low level medium high level level probability *** match filter back prop.
Proceedings 2003 International Conference on Image Processing, Oct 14, 2003
Existing binarization methods are categorized as either global or local. In this paper we present... more Existing binarization methods are categorized as either global or local. In this paper we present a new category, where the image is considered as a collection of sub-images. Each sub-image provides a statistical model for the handwritten characters that will be used to optimize the binarization of other sub-images. This method can be applied to different types of documents and
Iet Computer Vision, 2013
Ieee Transactions on Image Processing a Publication of the Ieee Signal Processing Society, Feb 1, 2007
In this paper, we generalize the iterative regularization method and the inverse scale space meth... more In this paper, we generalize the iterative regularization method and the inverse scale space method, recently developed for total-variation (TV) based image restoration, to wavelet-based image restoration. This continues our earlier joint work with others where we applied these techniques to variational-based image restoration, obtaining significant improvement over the Rudin-Osher-Fatemi TV-based restoration. Here, we apply these techniques to soft shrinkage and obtain the somewhat surprising result that a) the iterative procedure applied to soft shrinkage gives firm shrinkage and converges to hard shrinkage and b) that these procedures enhance the noise-removal capability both theoretically, in the sense of generalized Bregman distance, and for some examples, experimentally, in terms of the signal-to-noise ratio, leaving less signal in the residual.
Lecture Notes in Computer Science, 2010
This paper proposes an algorithm that fuses edge information into Markov Random Fields (MRF) regi... more This paper proposes an algorithm that fuses edge information into Markov Random Fields (MRF) region growing based image segmentation. The idea is to segment the image in a way that takes edge information into consideration. This is achieved by modifying the energy function minimization process so that it would penalize merging regions that have real edges in the boundary between them. Experimental results confirming the hypothesis that the addition of edge information increases the precision of the segmentation by ensuring the conservation of the objects contours during the region growing.
Binarization of document images with poor contrast, strong noise, complex patterns, and variable ... more Binarization of document images with poor contrast, strong noise, complex patterns, and variable modalities in the gray-scale histograms is a challenging problem. A new binarization algorithm has been developed to address this problem for personal cheque images. The main contribution of this approach is optimizing the binarization of a part of the document image that suffers from noise interference, referred to as the Target Sub-Image (TSI), using information easily extracted from another noise-free part of the same image, referred to as the Model Sub-Image (MSI). Simple spatial features extracted from MSI are used as a model for handwriting strokes. This model captures the underlying characteristics of the writing strokes, and is invariant to the handwriting style or content. This model is then utilized to guide the binarization in the TSI. Another contribution is a new technique for the structural analysis of document images, which we call "Wavelet Partial Reconstruction" (WPR). The algorithm was tested on 4,200 cheque images and the results show significant improvement in binarization quality in comparison with other well-established algorithms.
Proceedings of Sixth International Conference on Document Analysis and Recognition, 2001
Binarization of document images with poor contrast, strong noise complex patterns and variable mo... more Binarization of document images with poor contrast, strong noise complex patterns and variable modalities in the gray-scale histograms is a challenging problem. We present a binarization algorithm based on an image dependent model to address this problem for a cheque processing application. The proposed algorithm seeks an optimal threshold that would eliminate the background noise, while preserving as much character