Mani Deepak Choudhry^1,*, B. Aruna Devi², M. Sundarrajan³

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 267-278, 2022, DOI:10.32604/iasc.2022.024024 - 15 April 2022

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… More >

Tamer AbuKhalil¹, Bassam A. Y. Alqaralleh^2,*, Ahmad H. Al-Omari³

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 57-71, 2022, DOI:10.32604/cmc.2022.024367 - 24 February 2022

Abstract Prevention of cervical cancer becomes essential and is carried out by the use of Pap smear images. Pap smear test analysis is laborious and tiresome work performed visually using a cytopathologist. Therefore, automated cervical cancer diagnosis using automated methods are necessary. This paper designs an optimal deep learning based Inception model for cervical cancer diagnosis (ODLIM-CCD) using pap smear images. The proposed ODLIM-CCD technique incorporates median filtering (MF) based pre-processing to discard the noise and Otsu model based segmentation process. Besides, deep convolutional neural network (DCNN) based Inception with Residual Network (ResNet) v2 model is More >

Hesham Alhumyani^1,*, Ibrahim Alrube¹, Sameer Alsharif¹, Ashraf Afifi¹, Chokri Ben Amar¹, Hala S. El-Sayed², Osama S. Faragallah³

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4657-4673, 2022, DOI:10.32604/cmc.2022.020338 - 11 October 2021

Abstract The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of More >

Jinwei Wang^{1, 2, 3, 4}, Qiye Ni³, Yang Zhang³, Xiangyang Luo^{2, *}, Yunqing Shi⁵, Jiangtao Zhai³, Sunil Kr Jha³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 929-943, 2020, DOI:10.32604/cmc.2020.06569 - 23 July 2020

Abstract Median filtering is a nonlinear signal processing technique and has an advantage in the field of image anti-forensics. Therefore, more attention has been paid to the forensics research of median filtering. In this paper, a median filtering forensics method based on quaternion convolutional neural network (QCNN) is proposed. The median filtering residuals (MFR) are used to preprocess the images. Then the output of MFR is expanded to four channels and used as the input of QCNN. In QCNN, quaternion convolution is designed that can better mix the information of different channels than traditional methods. The More >

Jinwei Wang^{1, *}, Yang Zhang¹

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 99-112, 2020, DOI:10.32604/cmc.2020.04373

Abstract In the paper, a convolutional neural network based on quaternion transformation is proposed to detect median filtering for color images. Compared with conventional convolutional neural network, color images can be processed in a holistic manner in the proposed scheme, which makes full use of the correlation between RGB channels. And due to the use of convolutional neural network, it can effectively avoid the one-sidedness of artificial features. Experimental results have shown the scheme’s improvement over the state-of-the-art scheme on the accuracy of color image median filtering detection. More >

Wentao Ma¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Yuanjing Luo¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 665-677, 2019, DOI:10.32604/cmc.2019.05683

Abstract As the first barrier to protect cyberspace, the CAPTCHA has made significant contributions to maintaining Internet security and preventing malicious attacks. By researching the CAPTCHA, we can find its vulnerability and improve the security of CAPTCHA. Recently, many studies have shown that improving the image preprocessing effect of the CAPTCHA, which can achieve a better recognition rate by the state-of-the-art machine learning algorithms. There are many kinds of noise and distortion in the CAPTCHA images of this experiment. We propose an adaptive median filtering algorithm based on divide and conquer in this paper. Firstly, the More >