Hade Mao^{1, 2}, Yuliang Liu^{1, 2, *}, Hongzhe Yan^{1, 2}, Cheng Qian³, Jing Xue⁴

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 511-527, 2020, DOI:10.32604/cmc.2020.09841 - 23 July 2020

Abstract To troubleshoot two problems arising from the segmentation of manganese nodule images-uneven illumination and morphological defects caused by white sand coverage, we propose, with reference to features of manganese nodules, a method called “background gray value calculation”. As the result of the image procession with the aid this method, the two problems above are solved eventually, together with acquisition of a segmentable image of manganese nodules. As a result, its comparison with other segmentation methods justifies its feasibility and stability. Judging from simulation results, it is indicated that this method is applicable to repair the More >

Sanghyo Lee¹, Yonghan Ahn², Ha Young Kim^{3, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 1-17, 2020, DOI:10.32604/cmc.2020.011104 - 23 July 2020

Abstract In this study, we examined the efficacy of a deep convolutional neural network (DCNN) in recognizing concrete surface images and predicting the compressive strength of concrete. A digital single-lens reflex (DSLR) camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN. Thereafter, training, validation, and testing of the DCNNs were performed based on the DSLR camera and microscope image data. Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy. The accuracy of the DSLR-derived image data was attributed… More >

Xintao Duan^{1, *}, Daidou Guo¹, Chuan Qin²

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 721-745, 2020, DOI:10.32604/cmes.2020.09463 - 20 July 2020

Abstract Image steganography is a technique that hides secret information into the cover image to protect information security. The current image steganography is mainly to embed a smaller secret image in an area such as a texture of a larger-sized cover image, which will cause the size of the secret image to be much smaller than the cover image. Therefore, the problem of small steganographic capacity needs to be solved urgently. This paper proposes a steganography framework that combines image compression. In this framework, the Vector Quantized Variational AutoEncoder (VQ-VAE) is used to achieve the compression More >

Wei Fang^{1, 2, 3, ∗}, Lin Pang¹, Weinan Yi¹

Journal on Artificial Intelligence, Vol.2, No.1, pp. 39-58, 2020, DOI:10.32604/jai.2020.09789 - 15 July 2020

Abstract In recent years, with the rapid development of human society, more and more complex tasks have emerged that require deep learning to automatically extract abstract feature representations from a large amount of data, and use reinforcement learning to learn the best strategy to complete the task. Through the combination of deep learning and reinforcement learning, end-to-end input and output can be achieved, and substantial breakthroughs have been made in many planning and decision-making systems with infinite states, such as games, in particular, AlphaGo, robotics, natural language processing, dialogue systems, machine translation, and computer vision. In More >

Kui Fu¹, Jiansheng Peng^{1, 2, *}, Hanxiao Zhang², Xiaoliang Wang³, Frank Jiang⁴

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1977-1997, 2020, DOI:10.32604/cmc.2020.09882 - 30 June 2020

Abstract Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation More >

Desheng Zheng^{1, *}, Ziyong Ran¹, Zhifeng Liu¹, Liang Li², Lulu Tian³

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1885-1895, 2020, DOI:10.32604/cmc.2020.010070 - 30 June 2020

Abstract In the sorting system of the production line, the object movement, fixed angle of view, light intensity and other reasons lead to obscure blurred images. It results in bar code recognition rate being low and real time being poor. Aiming at the above problems, a progressive bar code compressed recognition algorithm is proposed. First, assuming that the source image is not tilted, use the direct recognition method to quickly identify the compressed source image. Failure indicates that the compression ratio is improper or the image is skewed. Then, the source image is enhanced to identify More >

Yun Tan¹, Jiaohua Qin^{1, *}, Hao Tang², Xuyu Xiang¹, Ling Tan², Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1797-1817, 2020, DOI:10.32604/cmc.2020.010802 - 30 June 2020

Abstract With the development of the internet of medical things (IoMT), the privacy protection problem has become more and more critical. In this paper, we propose a privacy protection scheme for medical images based on DenseNet and coverless steganography. For a given group of medical images of one patient, DenseNet is used to regroup the images based on feature similarity comparison. Then the mapping indexes can be constructed based on LBP feature and hash generation. After mapping the privacy information with the hash sequences, the corresponding mapped indexes of secret information will be packed together with More >

Ming Zhao¹, Xinhong Liu¹, Xin Yao^{1, *}, Kun He²

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1601-1614, 2020, DOI:10.32604/cmc.2020.09754 - 30 June 2020

Abstract Although there has been a great breakthrough in the accuracy and speed of super-resolution (SR) reconstruction of a single image by using a convolutional neural network, an important problem remains unresolved: how to restore finer texture details during image super-resolution reconstruction? This paper proposes an Enhanced Laplacian Pyramid Generative Adversarial Network (ELSRGAN), based on the Laplacian pyramid to capture the high-frequency details of the image. By combining Laplacian pyramids and generative adversarial networks, progressive reconstruction of super-resolution images can be made, making model applications more flexible. In order to solve the problem of gradient disappearance,… More >

Mohammad Shorfuzzaman^{1, *}, Mehedi Masud¹

CMC-Computers, Materials & Continua, Vol.64, No.3, pp. 1359-1381, 2020, DOI:10.32604/cmc.2020.011326 - 30 June 2020

Abstract Coronavirus disease (COVID-19) is an extremely infectious disease and possibly causes acute respiratory distress or in severe cases may lead to death. There has already been some research in dealing with coronavirus using machine learning algorithms, but few have presented a truly comprehensive view. In this research, we show how convolutional neural network (CNN) can be useful to detect COVID-19 using chest X-ray images. We leverage the CNN-based pre-trained models as feature extractors to substantiate transfer learning and add our own classifier in detecting COVID-19. In this regard, we evaluate performance of five different pre-trained… More >

Jianwei Zhang¹, Ze Qin¹, Shunfeng Wang^{1, *}

Journal of Cyber Security, Vol.2, No.1, pp. 25-36, 2020, DOI:10.32604/jcs.2020.06429

Abstract Digital images have been applied to various areas such as evidence in courts. However, it always suffers from noise by criminals. This type of computer network security has become a hot issue that can’t be ignored. In this paper, we focus on noise removal so as to provide guarantees for computer network security. Firstly, we introduce a well-known denoising method called Expected Patch Log Likelihood (EPLL) with Gaussian Mixture Model as its prior. This method achieves exciting results in noise removal. However, there remain problems to be solved such as preserving the edge and meaningful… More >