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  • Open Access


    Efficient Crack Severity Level Classification Using Bilayer Detection for Building Structures

    M. J. Anitha1,*, R. Hemalatha2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1183-1200, 2023, DOI:10.32604/csse.2023.031888

    Abstract Detection of cracks at the early stage is considered as very constructive since precautionary steps need to be taken to avoid the damage to the civil structures. Moreover, identifying and classifying the severity level of cracks is inevitable in order to find the stability of buildings. Hence, this paper proposes an efficient strategy to classify the cracks into fine, medium, and thick using a novel bilayer crack detection algorithm. The bilayer crack detection algorithm helps in extracting the requisite features from the crack for efficient classification. The proposed algorithm works well in the dark background and connects the discontinued cracks… More >

  • Open Access


    Salp Swarm Algorithm with Multilevel Thresholding Based Brain Tumor Segmentation Model

    Hanan T. Halawani*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6775-6788, 2023, DOI:10.32604/cmc.2023.030814

    Abstract Biomedical image processing acts as an essential part of several medical applications in supporting computer aided disease diagnosis. Magnetic Resonance Image (MRI) is a commonly utilized imaging tool used to save glioma for clinical examination. Biomedical image segmentation plays a vital role in healthcare decision making process which also helps to identify the affected regions in the MRI. Though numerous segmentation models are available in the literature, it is still needed to develop effective segmentation models for BT. This study develops a salp swarm algorithm with multi-level thresholding based brain tumor segmentation (SSAMLT-BTS) model. The presented SSAMLT-BTS model initially employs… More >

  • Open Access


    Detection and Classification of Hemorrhages in Retinal Images

    Ghassan Ahmed Ali1, Thamer Mitib Ahmad Al Sariera2,*, Muhammad Akram1, Adel Sulaiman1, Fekry Olayah1

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119

    Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images… More >

  • Open Access


    Fuzzy Hybrid Coyote Optimization Algorithm for Image Thresholding

    Linguo Li1,2, Xuwen Huang2, Shunqiang Qian2, Zhangfei Li2, Shujing Li2,*, Romany F. Mansour3

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3073-3090, 2022, DOI:10.32604/cmc.2022.026625

    Abstract In order to address the problems of Coyote Optimization Algorithm in image thresholding, such as easily falling into local optimum, and slow convergence speed, a Fuzzy Hybrid Coyote Optimization Algorithm (hereinafter referred to as FHCOA) based on chaotic initialization and reverse learning strategy is proposed, and its effect on image thresholding is verified. Through chaotic initialization, the random number initialization mode in the standard coyote optimization algorithm (COA) is replaced by chaotic sequence. Such sequence is nonlinear and long-term unpredictable, these characteristics can effectively improve the diversity of the population in the optimization algorithm. Therefore, in this paper we first… More >

  • Open Access


    Detection of Osteoarthritis Based on EHO Thresholding

    R. Kanthavel1,*, R. Dhaya2, Kanagaraj Venusamy3

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5783-5798, 2022, DOI:10.32604/cmc.2022.023745

    Abstract Knee Osteoarthritis (OA) is a joint disease that is commonly observed in people around the world. Osteoarthritis commonly affects patients who are obese and those above the age of 60. A valid knee image was generated by Computed Tomography (CT). In this work, efficient segmentation of CT images using Elephant Herding Optimization (EHO) optimization is implemented. The initial stage employs, the CT image normalization and the normalized image is incited to image enhancement through histogram correlation. Consequently, the enhanced image is segmented by utilizing Niblack and Bernsen algorithm. The (EHO) optimized outcome is evaluated in two steps. The initial step… More >

  • Open Access


    A Novel Hybrid Tunicate Swarm Naked Mole-Rat Algorithm for Image Segmentation and Numerical Optimization

    Supreet Singh1,2, Nitin Mittal1, Urvinder Singh2, Rohit Salgotra2, Atef Zaguia3, Dilbag Singh4,*

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3445-3462, 2022, DOI:10.32604/cmc.2022.023004

    Abstract This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm (TSNMRA) which uses hybridization concept of tunicate swarm algorithm (TSA) and naked mole-rat algorithm (NMRA). This newly developed algorithm uses the characteristics of both algorithms (TSA and NMRA) and enhance the exploration abilities of NMRA. Apart from the hybridization concept, important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing mutation operator and there is no need to define its value manually. For evaluating the working capabilities of proposed TSNMRA, it is tested for 100-digit challenge (CEC… More >

  • Open Access


    Curvelet Transform Based on Edge Preserving Filter for Retinal Blood Vessel Segmentation

    Sonali Dash1, Sahil Verma2,*, Kavita2, N. Z. Jhanjhi3, Mehedi Masud4, Mohammed Baz5

    CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2459-2476, 2022, DOI:10.32604/cmc.2022.020904

    Abstract Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral… More >

  • Open Access


    Handling Class Imbalance in Online Transaction Fraud Detection

    Kanika1, Jimmy Singla1, Ali Kashif Bashir2, Yunyoung Nam3,*, Najam UI Hasan4, Usman Tariq5

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2861-2877, 2022, DOI:10.32604/cmc.2022.019990

    Abstract With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem. In this research work, an… More >

  • Open Access


    Efficient Concurrent L1-Minimization Solvers on GPUs

    Xinyue Chu1, Jiaquan Gao1,*, Bo Sheng2

    Computer Systems Science and Engineering, Vol.38, No.3, pp. 305-320, 2021, DOI:10.32604/csse.2021.017144

    Abstract Given that the concurrent L1-minimization (L1-min) problem is often required in some real applications, we investigate how to solve it in parallel on GPUs in this paper. First, we propose a novel self-adaptive warp implementation of the matrix-vector multiplication (Ax) and a novel self-adaptive thread implementation of the matrix-vector multiplication (ATx), respectively, on the GPU. The vector-operation and inner-product decision trees are adopted to choose the optimal vector-operation and inner-product kernels for vectors of any size. Second, based on the above proposed kernels, the iterative shrinkage-thresholding algorithm is utilized to present two concurrent L1-min solvers from the perspective of the… More >

  • Open Access


    An Improved Jellyfish Algorithm for Multilevel Thresholding of Magnetic Resonance Brain Image Segmentations

    Mohamed Abdel-Basset1, Reda Mohamed1, Mohamed Abouhawwash2,3, Ripon K. Chakrabortty4, Michael J. Ryan4, Yunyoung Nam5,*

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2961-2977, 2021, DOI:10.32604/cmc.2021.016956

    Abstract Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel… More >

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