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  • Open Access

    ARTICLE

    Weber Law Based Approach for Multi-Class Image Forgery Detection

    Arslan Akram1,3, Javed Rashid2,3,4, Arfan Jaffar1, Fahima Hajjej5, Waseem Iqbal6, Nadeem Sarwar7,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 145-166, 2024, DOI:10.32604/cmc.2023.041074

    Abstract Today’s forensic science introduces a new research area for digital image analysis for multimedia security. So, Image authentication issues have been raised due to the wide use of image manipulation software to obtain an illegitimate benefit or create misleading publicity by using tempered images. Exiting forgery detection methods can classify only one of the most widely used Copy-Move and splicing forgeries. However, an image can contain one or more types of forgeries. This study has proposed a hybrid method for classifying Copy-Move and splicing images using texture information of images in the spatial domain. Firstly, images are divided into equal… More >

  • Open Access

    ARTICLE

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

    Shaik Mahaboob Basha1,*, Victor Hugo C. de Albuquerque2, Samia Allaoua Chelloug3,*, Mohamed Abd Elaziz4,5,6,7, Shaik Hashmitha Mohisin8, Suhail Parvaze Pathan9

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1981-2004, 2024, DOI:10.32604/cmes.2023.031425

    Abstract Manual investigation of chest radiography (CXR) images by physicians is crucial for effective decision-making in COVID-19 diagnosis. However, the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques. This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies, including normal cases. Texture information is extracted using gray co-occurrence matrix (GLCM)-based features, while vessel-like features are obtained using Frangi, Sato, and Meijering filters. Machine learning models employing Decision Tree (DT) and Random Forest (RF) approaches are designed to categorize CXR images into common lung infections, lung… More > Graphic Abstract

    Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

  • Open Access

    ARTICLE

    Recognizing Breast Cancer Using Edge-Weighted Texture Features of Histopathology Images

    Arslan Akram1,2, Javed Rashid2,3,4, Fahima Hajjej5, Sobia Yaqoob1,6, Muhammad Hamid7, Asma Irshad8, Nadeem Sarwar9,*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1081-1101, 2023, DOI:10.32604/cmc.2023.041558

    Abstract Around one in eight women will be diagnosed with breast cancer at some time. Improved patient outcomes necessitate both early detection and an accurate diagnosis. Histological images are routinely utilized in the process of diagnosing breast cancer. Methods proposed in recent research only focus on classifying breast cancer on specific magnification levels. No study has focused on using a combined dataset with multiple magnification levels to classify breast cancer. A strategy for detecting breast cancer is provided in the context of this investigation. Histopathology image texture data is used with the wavelet transform in this technique. The proposed method comprises… More >

  • Open Access

    PROCEEDINGS

    Self-Driving Behavior and Pinning Effect of Droplets on GrapheneCovered Functional Textured Surfaces

    Fujian Zhang1, Xiang Gao1, Zhongqiang Zhang1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09169

    Abstract Biological features such as the bumps on the back of desert beetles and the spikes of cacti enable the directional transport of water droplets, creating conditions for their survival in nature. Inspired by the interesting natural phenomenon, a novel design of nanopillared surface with a gradient density of structural pillar matrix covered by a monolayer graphene is proposed to realize ultrafast self-driving of water droplets. The droplet can move spontaneously at ultrahigh speed of 75.7 m/s (272.52 km/h) from sparsest to densest regions of pillars while a wettability gradient is created by the gradient distribution density of pillar matrix relying… More >

  • Open Access

    PROCEEDINGS

    Shear Localization in Polycrystalline Metal at High-Strain Rates with Dynamic Recrystallization: Crystal Plasticity Modeling and Texture Effect

    Qilin Xiong1,2,*, Wen An1,2, Chuanzhi Liu1,2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.3, pp. 1-1, 2023, DOI:10.32604/icces.2023.010044

    Abstract Shear localization is an important failure mode, or even the dominant mode in metals at high-strain rates. However, it is a great challenge to accurately predict the occurrence and evolution of shear localization in metals at the high-strain rate deformation. Here, a dislocation-based crystal plasticity constitutive model with a crucial mechanism of shear instability, namely dynamic recrystallization, was developed. The evolution equations of dislocation density and grain size in the process of dynamic recrystallization were proposed and incorporated into the new constitutive model. The threshold of the stored energy in crystals was used as the criterion for the occurrence of… More >

  • Open Access

    ARTICLE

    Classification-Detection of Metal Surfaces under Lower Edge Sharpness Using a Deep Learning-Based Approach Combined with an Enhanced LoG Operator

    Hong Zhang1,*, Jiaming Zhou1, Qi Wang1, Chengxi Zhu1, Haijian Shao2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1551-1572, 2023, DOI:10.32604/cmes.2023.027035

    Abstract Metal flat surface in-line surface defect detection is notoriously difficult due to obstacles such as high surface reflectivity, pseudo-defect interference, and random elastic deformation. This study evaluates the approach for detecting scratches on a metal surface in order to address a problem in the detection process. This paper proposes an improved Gauss-Laplace (LoG) operator combined with a deep learning technique for metal surface scratch identification in order to solve the difficulties that it is challenging to reduce noise and that the edges are unclear when utilizing existing edge detection algorithms. In the process of scratch identification, it is challenging to… More >

  • Open Access

    ARTICLE

    Traffic Sign Detection with Low Complexity for Intelligent Vehicles Based on Hybrid Features

    Sara Khalid1, Jamal Hussain Shah1,*, Muhammad Sharif1, Muhammad Rafiq2, Gyu Sang Choi3,*

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 861-879, 2023, DOI:10.32604/cmc.2023.035595

    Abstract Globally traffic signs are used by all countries for healthier traffic flow and to protect drivers and pedestrians. Consequently, traffic signs have been of great importance for every civilized country, which makes researchers give more focus on the automatic detection of traffic signs. Detecting these traffic signs is challenging due to being in the dark, far away, partially occluded, and affected by the lighting or the presence of similar objects. An innovative traffic sign detection method for red and blue signs in color images is proposed to resolve these issues. This technique aimed to devise an efficient, robust and accurate… More >

  • Open Access

    ARTICLE

    Real-Time Multi-Feature Approximation Model-Based Efficient Brain Tumor Classification Using Deep Learning Convolution Neural Network Model

    Amarendra Reddy Panyala1,2, M. Baskar3,*

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 3883-3899, 2023, DOI:10.32604/csse.2023.037050

    Abstract The deep learning models are identified as having a significant impact on various problems. The same can be adapted to the problem of brain tumor classification. However, several deep learning models are presented earlier, but they need better classification accuracy. An efficient Multi-Feature Approximation Based Convolution Neural Network (CNN) model (MFA-CNN) is proposed to handle this issue. The method reads the input 3D Magnetic Resonance Imaging (MRI) images and applies Gabor filters at multiple levels. The noise-removed image has been equalized for its quality by using histogram equalization. Further, the features like white mass, grey mass, texture, and shape are… More >

  • Open Access

    ARTICLE

    Classification of Gastric Lesions Using Gabor Block Local Binary Patterns

    Muhammad Tahir1,*, Farhan Riaz2, Imran Usman1,3, Mohamed Ibrahim Habib1

    Computer Systems Science and Engineering, Vol.46, No.3, pp. 4007-4022, 2023, DOI:10.32604/csse.2023.032359

    Abstract The identification of cancer tissues in Gastroenterology imaging poses novel challenges to the computer vision community in designing generic decision support systems. This generic nature demands the image descriptors to be invariant to illumination gradients, scaling, homogeneous illumination, and rotation. In this article, we devise a novel feature extraction methodology, which explores the effectiveness of Gabor filters coupled with Block Local Binary Patterns in designing such descriptors. We effectively exploit the illumination invariance properties of Block Local Binary Patterns and the inherent capability of convolutional neural networks to construct novel rotation, scale and illumination invariant features. The invariance characteristics of… More >

  • Open Access

    ARTICLE

    Image Splicing Detection Using Generalized Whittaker Function Descriptor

    Dumitru Baleanu1,2,3, Ahmad Sami Al-Shamayleh4, Rabha W. Ibrahim5,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3465-3477, 2023, DOI:10.32604/cmc.2023.037162

    Abstract Image forgery is a crucial part of the transmission of misinformation, which may be illegal in some jurisdictions. The powerful image editing software has made it nearly impossible to detect altered images with the naked eye. Images must be protected against attempts to manipulate them. Image authentication methods have gained popularity because of their use in multimedia and multimedia networking applications. Attempts were made to address the consequences of image forgeries by creating algorithms for identifying altered images. Because image tampering detection targets processing techniques such as object removal or addition, identifying altered images remains a major challenge in research.… More >

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