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Analysis of BrainMRI: AI-Assisted Healthcare Framework for the Smart Cities

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Intelligent Automation & Soft Computing 2023年第2期35卷 1843-1856页

作者： Walid el-Shafai Randa Ali Ahmed Sedik Taha el-Sayed Taha Mohammed abd-elnaby fathi e.abd el-sam.e Department electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of ROBOTICS and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafrelsheikhEgypt Department of Computer engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

The use of intelligent machines to work and react like humans is vital in emerging smart ***-aided analysis of complex and huge MRI(Mag-netic Resonance Imaging)scans is very important in healthcare *** AI(Artiﬁcial Intelligence)driven healthcare applications,tumor detection is one of the contemporary researchﬁelds that have become attractive to *** are several modalities of imaging performed on the brain for the pur-pose of tumor *** paper offers a deep learning approach for detecting brain tumors from MR(Magnetic Resonance)images based on changes in the division of the training and testing data and the structure of the CNN(Convolu-tional Neural Network)*** proposed approach is carried out on a brain tumor dataset from the National Centre of Image-Guided Therapy,including about 4700 MRI images of ten brain tumor cases with both normal and abnormal *** dataset is divided into test,and train subsets with a ratio of the training set to the validation set of 70:*** main contribution of this paper is introdu-cing an optimum deep learning structure of CNN *** simulation results are obtained for 50 epochs in the training *** simulation results reveal that the optimum CNN architecture consists of four layers.

关键词： Healthcare smart cities clinical automation CNN machine learning brain tumor medical diagnosis

Cancelable Speaker Identification System Based on Optical-Like encryption Algorithms

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Computer Systems Science & engineering 2022年第10期43卷 87-102页

作者： Safaa el-Gazar Walid el-Shafai Ghada el-Banby Hesham F.A.Hamed Gerges M.Salama Mohammed abd-elnaby fathi e.abd el-sam.e Department of electrical engineering Faculty of EngineeringEgyptian-Russian UniversityCairoEgypt Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Computer engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Biometric authentication is a rapidly growing trend that is gaining increasing attention in the last *** achieves safe access to systems using biometrics instead of the traditional *** utilization of a biometric in its original format makes it usable only ***,a cancelable biometric template should be used,so that it can be replaced when it is *** biometrics aims to enhance the security and privacy of biometric *** encryption is an efficient technique to be used in order to generate cancelable biometric *** this paper,a highly-secure encryption algorithm is proposed to ensure secure biometric data in verification *** considered biometric in this paper is the speech *** speech signal is transformed into its ***,the spectrogram is encrypted using two cascaded optical encryption *** first algorithm is the Optical Scanning Holography(OSH)for its efficiency as an encryption *** OSH encrypted spectrogram is encrypted using Double Random Phase encoding(DRPe)by implementing two Random Phase Masks(RPMs).After the two cascaded optical encryption algorithms,the cancelable template is *** verification is implemented through correlation estimation between enrolled and test templates in their encrypted *** the correlation value is larger than a threshold value,the user is *** threshold value can be determined from the genuine and imposter correlation distribution curves as the midpoint between the two *** implementation of optical encryption is adopted using its software rather than the optical *** efficiency of the proposed cancelable biometric algorithm is illustrated by the simulation *** can improve the biometric data security without deteriorating the recognition *** results give close-to-zero This values for the equal error Rate(eeR)and close-to-one values for the Area under Receiver Operator Charact

关键词： Cancelable biometrics spectrogram OSH DRPe eeR AROC

A Hybrid Security Framework for Medical Image Communication

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Computers, Materials & Continua 2022年第11期73卷 2713-2730页

作者： Walid el-Shafai Hayam A.abd el-Hameed Ashraf A.M.Khalaf Naglaa F.Soliman Amel A.Alhussan fathi e.abd el-sam.e Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia electrical Communications engineering Department Faculty of EngineeringMinia UniversityMinia61111Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

Authentication of the digital image has much attention for the digital *** image authentication can be verified with image watermarking and image encryption *** schemes are widely used to protect images against forgery attacks,and they are useful for protecting copyright and rightful *** on the desirable applications,several image encryption and watermarking schemes have been proposed to moderate this *** framework presents a new scheme that combines a Walsh Hadamard Transform(WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase encoding(DRPe).First,on the sender side,the secret medical image is encrypted using *** the encrypted image is watermarking based on *** combination between watermarking and encryption increases the security and robustness of transmitting an *** performance evaluation of the proposed scheme is obtained by testing Structural Similarity Index(SSIM),Peak Signal-to-Noise Ratio(PSNR),Normalized cross-correlation(NC),and Feature Similarity Index(FSIM).

关键词： Walsh hadamard transform watermarking encryption double random phase encoding structural similarity index

efficient Forgery Detection Approaches for Digital Color Images

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Computers, Materials & Continua 2022年第5期71卷 3257-3276页

作者： Amira Baumy Abeer D.Algarni Mahmoud abdalla Walid el-Shafai fathi e.abd el-sam.e Naglaa F.Soliman Department of Communications High Institute for Engineering and TechnologyAl-Obour Obour CityEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Department of electronics and Communications engineering Faculty of EngineeringZagazig UniversityZagazigSharqia44519Egypt Department of electronics and electrical Communications engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Security engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia

This paper is concerned with a vital topic in image processing:color image forgery detection. The development of computing capabilitieshas led to a breakthrough in hacking and forgery attacks on signal, image,and data communicated over networks. Hence, there is an urgent need fordeveloping efficient image forgery detection algorithms. Two main types offorgery are considered in this paper: splicing and copy-move. Splicing isperformed by inserting a part of an image into another image. On the otherhand, copy-move forgery is performed by copying a part of the image intoanother position in the same image. The proposed approach for splicingdetection is based on the assumption that illumination between the originaland tampered images is different. To detect the difference between the originaland tampered images, the homomorphic transform separates the illuminationcomponent from the reflectance component. The illumination histogramderivative is used for detecting the difference in illumination, and henceforgery detection is accomplished. Prior to performing the forgery detectionprocess, some pre-processing techniques, including histogram equalization,histogram matching, high-pass filtering, homomorphic enhancement, andsingle image super-resolution, are introduced to reinforce the details andchanges between the original and embedded sections. The proposed approachfor copy-move forgery detection is performed with the Speeded Up RobustFeatures (SURF) algorithm, which extracts feature points and feature vectors. Searching for the copied partition is accomplished through matchingwith euclidian distance and hierarchical clustering. In addition, some preprocessing methods are used with the SURF algorithm, such as histogramequalization and single-mage super-resolution. Simulation results proved thefeasibility and the robustness of the pre-processing step in homomorphicdetection and SURF detection algorithms for splicing and copy-move forgerydetection, respectively.

关键词： Image forgery splicing algorithm copy-move algorithm histogram matching homomorphic enhancement SISR SURF

An efficient GCD-Based Cancelable Biometric Algorithm for Single and Multiple Biometrics

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Computers, Materials & Continua 2021年第11期69卷 1571-1595页

作者： Naglaa F.Soliman Abeer D.Algarni Walid el-Shafai fathi e.abd el-sam.e Ghada M.el Banby Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt

Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things(IoT)*** objective of using cancelable biometrics is to save the original ones from hacking attempts.A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT *** original biometric is blurred with two co-prime ***,it can be recovered as the Greatest Common Divisor(GCD)between its two blurred *** changes if induced in the biometric image prior to processing with co-prime operators prevents the recovery of the original biometric image through a GCD ***,the ability to change cancelable templates is guaranteed,since the owner of the biometric can pre-determine and manage the minimal change induced in the biometric ***,we test the utility of the proposed algorithm in the single-and multi-biometric *** multi-biometric scenario depends on compressing face,fingerprint,iris,and palm print images,simultaneously,to generate the cancelable *** metrics such as equal error Rate(eeR)and Area and Receiver Operator Characteristic curve(AROC)are *** results on single-and multi-biometric scenarios show high AROC values up to 99.59%,and low eeR values down to 0.04%.

关键词： Cloud IoT cancelable biometrics GCD single-and multi-biometrics security applications

An efficient CNN-Based Hybrid Classification and Segmentation Approach for COVID-19 Detection

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Computers, Materials & Continua 2022年第3期70卷 4393-4410页

作者： Abeer D.Algarni Walid el-Shafai Ghada M.el Banby fathi e.abd el-sam.e Naglaa F.Soliman Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh 84428Saudi Arabia Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf 32952Egypt Department of electronics and Communications engineering Faculty of EngineeringZagazig UniversityZagazigSharqia 44519Egypt

COVID-19 remains to proliferate precipitously in the *** has significantly influenced public health,the world economy,and the persons’***,there is a need to speed up the diagnosis and precautions to deal with COVID-19 *** this explosion of this pandemic,there is a need for automated diagnosis tools to help specialists based onmedical *** paper presents a hybrid Convolutional Neural Network(CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography(CT)*** proposed approach is employed to classify and segment the COVID-19,pneumonia,and normal CT *** classification stage is firstly applied to detect and classify the input medical CT ***,the segmentation stage is performed to distinguish between pneumonia and COVID-19 CT *** classification stage is implemented based on a simple and efficient CNN deep learning *** model comprises four Rectified Linear Units(RelUs),four batch normalization layers,and four convolutional(Conv)*** layer depends on filters with sizes of 64,32,16,and 8.A2×2windowand a stride of 2 are employed in the utilized four max-pooling layers.A soft-max activation function and a Fully-Connected(FC)layer are utilized in the classification stage to perform the detection *** the segmentation process,the Simplified Pulse Coupled Neural Network(SPCNN)is utilized in the proposed hybrid *** proposed segmentation approach is based on salient object detection to localize the COVID-19 or pneumonia region,*** summarize the contributions of the paper,we can say that the classification process with a CNN model can be the first stage a highly-effective automated diagnosis *** the images are accepted by the system,it is possible to perform further processing through a segmentation process to isolate the regions of interest in the *** region of interest can be assesses both automatically and through ***

关键词： COVID-19 segmentation classification CNN SPCNN CT images

enhanced Robotic Vision System Based on Deep Learning and Image Fusion

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Computers, Materials & Continua 2022年第10期73卷 1845-1861页

作者： e.A.Alabdulkreem Ahmed Sedik Abeer D.Algarni Ghada M.el Banby fathi e.abd el-sam.e Naglaa F.Soliman Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafrelsheikh33511Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Image fusion has become one of the interesting fields that attract researchers to integrate information from different image *** is involved in several *** of the recent applications is the robotic *** application necessitates image enhancement of both infrared(IR)and visible *** paper presents a Robot Human Interaction System(RHIS)based on image fusion and deep *** basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured ***,an enhancement model is carried out on the fused image to increase its *** image enhancement models such as fuzzy logic,Convolutional Neural Network(CNN)and residual network(ResNet)pre-trained model are utilized on the fusion results and they are compared with each other and with the state-of-the-art *** results prove that the fuzzy logic enhancement gives the best results from the image quality ***,the proposed system can be considered as an efficient solution for the robotic vision problem with multi-modality images.

关键词： Deep learning fuzzy logic image fusion IR images

Secure and Robust Optical Multi-Stage Medical Image Cryptosystem

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Computers, Materials & Continua 2022年第1期70卷 895-913页

作者： Walid el-Shafai Moustafa H.Aly Abeer D.Algarni fathi e.abd el-sam.e Naglaa F.Soliman Department electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and Communications engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Due to the rapid growth of telemedicine and healthcare services,color medical image security applications have been expanded *** this paper,an asymmetric PTFrFT(Phase Truncated Fractional Fourier Transform)-based color medical image cryptosystem is *** different phases in the fractional Fourier and output planes are provided as deciphering ***,the ciphering keys will not be employed for the deciphering ***,the introduced PTFrFT algorithm comprises asymmetric ciphering and deciphering processes in contrast to the traditional optical symmetric OSH(Optical Scanning Holography)and DRPe(Double Random Phase encoding)*** of the principal impacts of the introduced asymmetric cryptosystem is that it eliminates the onedimensionality aspects of the related symmetric cryptosystems due to its remarkable feature of phase nonlinear truncation *** comparisons on various colormedical images are examined and analyzed to substantiate the cryptosystem *** achieved experimental outcomes ensure that the introduced cryptosystem is robust and *** has terrific cryptography performance compared to conventional cryptography algorithms,even in the presence of noise and severe channel attacks.

关键词： Optical encryption medical image security symmetric and asymmetric encryption OSH DRPe PTFrFT

efficient Deep Learning Modalities for Object Detection from Infrared Images

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Computers, Materials & Continua 2022年第8期72卷 2545-2563页

作者： Naglaa F.Soliman e.A.Alabdulkreem Abeer D.Algarni Ghada M.el Banby fathi e.abd el-sam.e Ahmed Sedik Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Industrial electronics and Control engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of electronics and electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelSheikh UniversityKafr el-sheikhEgypt

For military warfare purposes,it is necessary to identify the type of a certain weapon through video stream tracking based on infrared(IR)video *** vision is a visual search trend that is used to identify objects in images or video *** military applications,drones take a main role in surveillance tasks,but they cannot be confident for longtime ***,there is a need for such a system,which provides a continuous surveillance task to support the drone *** a system can be called a Hybrid Surveillance System(HSS).This system is based on a distributed network of wireless sensors for continuous *** addition,it includes one or more drones to make short-time missions,if the sensors detect a suspicious *** paper presents a digital solution to identify certain types of concealed weapons in surveillance applications based on Convolutional Neural Networks(CNNs)and Convolutional Long Short-Term Memory(ConvLSTM).Based on initial results,the importance of video frame enhancement is obvious to improve the visibility of objects in video *** accuracy of the proposed methods reach 99%,which reflects the effectiveness of the presented *** addition,the experimental results prove that the proposed methods provide superior performance compared to traditional ones.

关键词： Deep learning object detection military applications OFDM SPIHT IoT