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  • Open Access

    ARTICLE

    Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

    Ahmed H. Alhadethi1,*, Ikram Smaoui2, Ahmed Fakhfakh3, Saad M. Darwish4

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4825-4844, 2024, DOI:10.32604/cmc.2024.047852 - 20 June 2024

    Abstract The act of transmitting photos via the Internet has become a routine and significant activity. Enhancing the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further enhanced. This study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous images. The main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image compression. This paper introduces… More >

  • Open Access

    ARTICLE

    Robust Interactive Method for Hand Gestures Recognition Using Machine Learning

    Amal Abdullah Mohammed Alteaimi1,*, Mohamed Tahar Ben Othman1,2

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 577-595, 2022, DOI:10.32604/cmc.2022.023591 - 24 February 2022

    Abstract The Hand Gestures Recognition (HGR) System can be employed to facilitate communication between humans and computers instead of using special input and output devices. These devices may complicate communication with computers especially for people with disabilities. Hand gestures can be defined as a natural human-to-human communication method, which also can be used in human-computer interaction. Many researchers developed various techniques and methods that aimed to understand and recognize specific hand gestures by employing one or two machine learning algorithms with a reasonable accuracy. This work aims to develop a powerful hand gesture recognition model with… More >

  • Open Access

    ARTICLE

    Video Surveillance-Based Urban Flood Monitoring System Using a Convolutional Neural Network

    R. Dhaya1,*, R. Kanthavel2

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 183-192, 2022, DOI:10.32604/iasc.2022.021538 - 26 October 2021

    Abstract The high prevalence of urban flooding in the world is increasing rapidly with the rise in extreme weather events. Consequently, this research uses an Automatic Flood Monitoring System (ARMS) through a video surveillance camera. Initially, videos are collected from a surveillance camera and converted into video frames. After converting the video frames, the water level can be identified by using a Histogram of oriented Gradient (HoG), which is used to remove the functionality. Completing the extracted features, the frames are enhanced by using a median filter to remove the unwanted noise from the image. The More >

  • Open Access

    ARTICLE

    Traffic Flow Statistics Method Based on Deep Learning and Multi-Feature Fusion

    Liang Mu, Hong Zhao*, Yan Li, Xiaotong Liu, Junzheng Qiu, Chuanlong Sun

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 465-483, 2021, DOI:10.32604/cmes.2021.017276 - 08 October 2021

    Abstract Traffic flow statistics have become a particularly important part of intelligent transportation. To solve the problems of low real-time robustness and accuracy in traffic flow statistics. In the DeepSort tracking algorithm, the Kalman filter (KF), which is only suitable for linear problems, is replaced by the extended Kalman filter (EKF), which can effectively solve nonlinear problems and integrate the Histogram of Oriented Gradient (HOG) of the target. The multi-target tracking framework was constructed with YOLO V5 target detection algorithm. An efficient and long-running Traffic Flow Statistical framework (TFSF) is established based on the tracking framework.… More >

  • Open Access

    ARTICLE

    Pashto Characters Recognition Using Multi-Class Enabled Support Vector Machine

    Sulaiman Khan1, Shah Nazir1, Habib Ullah Khan2,*, Anwar Hussain1

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2831-2844, 2021, DOI:10.32604/cmc.2021.015054 - 01 March 2021

    Abstract During the last two decades significant work has been reported in the field of cursive language’s recognition especially, in the Arabic, the Urdu and the Persian languages. The unavailability of such work in the Pashto language is because of: the absence of a standard database and of significant research work that ultimately acts as a big barrier for the research community. The slight change in the Pashto characters’ shape is an additional challenge for researchers. This paper presents an efficient OCR system for the handwritten Pashto characters based on multi-class enabled support vector machine using… More >

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