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  • Open Access


    Multiple Forgery Detection in Video Using Convolution Neural Network

    Vinay Kumar1,*, Vineet Kansal2, Manish Gaur2

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1347-1364, 2022, DOI:10.32604/cmc.2022.023545

    Abstract With the growth of digital media data manipulation in today’s era due to the availability of readily handy tampering software, the authenticity of records is at high risk, especially in video. There is a dire need to detect such problem and do the necessary actions. In this work, we propose an approach to detect the interframe video forgery utilizing the deep features obtained from the parallel deep neural network model and thorough analytical computations. The proposed approach only uses the deep features extracted from the CNN model and then applies the conventional mathematical approach to these features to find the… More >

  • Open Access


    Background Subtraction in Surveillance Systems Using Local Spectral Histograms and Linear Regression

    S. Hariharan1,*, R. Venkatesan2

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 407-422, 2022, DOI:10.32604/iasc.2022.025309

    Abstract Background subtraction is a fundamental and crucial task for computer vision-based automatic video analysis due to various challenging situations that occur in real-world scenarios. This paper presents a novel background subtraction method by estimating the background model using linear regression and local spectral histogram which captures combined spectral and texture features. Different linear filters are applied on the image window centered at each pixel location and the features are captured via these filter responses. Each feature has been approximated by a linear combination of two representative features, each of which corresponds to either a background or a foreground pixel. These… More >

  • Open Access


    Novel Optimized Framework for Video Processing in IoRT Driven Hospitals

    Mani Deepak Choudhry1,*, B. Aruna Devi2, M. Sundarrajan3

    Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 267-278, 2022, DOI:10.32604/iasc.2022.024024

    Abstract Internet of Remote things (IoRT) has gained recent attention and is considered as one most prominent research topics being carried out by numerous researchers worldwide. IoRT is being used in various applications and this paper mainly concentrates on the healthcare industry wherein it could be used effectively for patient monitoring. IoRT plays a crucial role in monitoring the patients in any healthcare center remotely by allowing simultaneous video transmissions possible from the emergency areas like Intensive Care Unit (ICU). Considering general scenarios, the video transmissions are done by the main use of Gaussian distribution. With the help of the proposed… More >

  • Open Access


    Sparse Crowd Flow Analysis of Tawaaf of Kaaba During the COVID-19 Pandemic

    Durr-e-Nayab1, Ali Mustafa Qamar2,*, Rehan Ullah Khan3, Waleed Albattah3, Khalil Khan4, Shabana Habib3, Muhammad Islam5

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5581-5601, 2022, DOI:10.32604/cmc.2022.022153

    Abstract The advent of the COVID-19 pandemic has adversely affected the entire world and has put forth high demand for techniques that remotely manage crowd-related tasks. Video surveillance and crowd management using video analysis techniques have significantly impacted today's research, and numerous applications have been developed in this domain. This research proposed an anomaly detection technique applied to Umrah videos in Kaaba during the COVID-19 pandemic through sparse crowd analysis. Managing the Kaaba rituals is crucial since the crowd gathers from around the world and requires proper analysis during these days of the pandemic. The Umrah videos are analyzed, and a… More >

  • Open Access


    Hardware Acceleration of Image and Video Processing on Xilinx Zynq Platform

    Praveenkumar Babu, Eswaran Parthasarathy*

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 1063-1071, 2021, DOI:10.32604/iasc.2021.018903

    Abstract Advancements in image and video processing are growing over the years for industrial robots, autonomous vehicles, indexing databases, surveillance, medical imaging and computer-human interaction applications. One of the major challenges in real-time image and video processing is the execution of complex functions and high computational tasks. In this paper, the hardware acceleration of different filter algorithms for both image and video processing is implemented on Xilinx Zynq®-7000 System on-Chip (SoC) device. It consists of Dual-core Cortex-A9 processors which provide computing ability to perform I/O and processing functions and software libraries using Vivado® High-Level Synthesis (HLS). In the proposed work, Sobel-Feldman… More >

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