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Search Results (11)
  • Open Access


    Improving Video Watermarking through Galois Field GF(24) Multiplication Tables with Diverse Irreducible Polynomials and Adaptive Techniques

    Yasmin Alaa Hassan1,*, Abdul Monem S. Rahma2

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1423-1442, 2024, DOI:10.32604/cmc.2023.046149

    Abstract Video watermarking plays a crucial role in protecting intellectual property rights and ensuring content authenticity. This study delves into the integration of Galois Field (GF) multiplication tables, especially GF(24), and their interaction with distinct irreducible polynomials. The primary aim is to enhance watermarking techniques for achieving imperceptibility, robustness, and efficient execution time. The research employs scene selection and adaptive thresholding techniques to streamline the watermarking process. Scene selection is used strategically to embed watermarks in the most vital frames of the video, while adaptive thresholding methods ensure that the watermarking process adheres to imperceptibility criteria, maintaining the video’s visual quality.… More >

  • 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


    A Novel Segment White Matter Hyperintensities Approach for Detecting Alzheimer

    Antonitta Eileen Pious1,*, U. K. Sridevi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2715-2726, 2023, DOI:10.32604/csse.2023.026582

    Abstract Segmentation has been an effective step that needs to be done before the classification or detection of an anomaly like Alzheimer’s on a brain scan. Segmentation helps detect pixels of the same intensity or volume and group them together as one class or region, where in that particular region of interest (ROI) can be concentrated on, rather than focusing on the entire image. In this paper White Matter Hyperintensities (WMH) is taken as a strong biomarker that supports and determines the presence of Alzheimer’s. As the first step a proper segmentation of the lesions has to be carried out. As… More >

  • Open Access


    A Sea Ice Recognition Algorithm in Bohai Based on Random Forest

    Tao Li1, Di Wu1, Rui Han2, Jinyue Xia3, Yongjun Ren4,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3721-3739, 2022, DOI:10.32604/cmc.2022.029619

    Abstract As an important maritime hub, Bohai Sea Bay provides great convenience for shipping and suffers from sea ice disasters of different severity every winter, which greatly affects the socio-economic and development of the region. Therefore, this paper uses FY-4A (a weather satellite) data to study sea ice in the Bohai Sea. After processing the data for land removal and cloud detection, it combines multi-channel threshold method and adaptive threshold algorithm to realize the recognition of Bohai Sea ice under clear sky conditions. The random forests classification algorithm is introduced in sea ice identification, which can achieve a certain effect of… 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


    Edge Detection of COVID-19 CT Image Based on GF_SSR, Improved Multiscale Morphology, and Adaptive Threshold

    Shouming Hou1, Chaolan Jia1, Kai Li1, Liya Fan2, Jincheng Guo3,*, Mackenzie Brown4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 81-94, 2022, DOI:10.32604/cmes.2022.019006

    Abstract Edge detection is an effective method for image segmentation and feature extraction. Therefore, extracting weak edges with the inhomogeneous gray of Corona Virus Disease 2019 (COVID-19) CT images is extremely important. Multiscale morphology has been widely used in the edge detection of medical images due to its excellent boundary detection accuracy. In this paper, we propose a weak edge detection method based on Gaussian filtering and singlescale Retinex (GF_SSR), and improved multiscale morphology and adaptive threshold binarization (IMSM_ATB). As all the CT images have noise, we propose to remove image noise by Gaussian filtering. The edge of CT images is… More >

  • Open Access


    Reversible Data Hiding in Encrypted Images Based on Adaptive Prediction-error Label Map

    Yu Ren1, Jiaohua Qin1,*, Yun Tan1, Neal N. Xiong2

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1439-1453, 2022, DOI:10.32604/iasc.2022.025485

    Abstract In the field of reversible data hiding in encrypted images (RDH-EI), predict an image effectively and embed a message into the image with lower distortion are two crucial aspects. However, due to the linear regression prediction being sensitive to outliers, it is a challenge to improve the accuracy of predictions. To address this problem, this paper proposes an RDH-EI scheme based on adaptive prediction-error label map. In the prediction stage, an adaptive threshold estimation algorithm based on local complexity is proposed. Then, the pixels selection method based on gradient of image is designed to train the parameters of the prediction… More >

  • Open Access


    Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold

    Usman Ali, Muhammad Tariq Mahmood*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219

    Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur, that may… More >

  • Open Access


    Defocus Blur Segmentation Using Genetic Programming and Adaptive Threshold

    Muhammad Tariq Mahmood*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4867-4882, 2022, DOI:10.32604/cmc.2022.019544

    Abstract Detection and classification of the blurred and the non-blurred regions in images is a challenging task due to the limited available information about blur type, scenarios and level of blurriness. In this paper, we propose an effective method for blur detection and segmentation based on transfer learning concept. The proposed method consists of two separate steps. In the first step, genetic programming (GP) model is developed that quantify the amount of blur for each pixel in the image. The GP model method uses the multi-resolution features of the image and it provides an improved blur map. In the second phase,… More >

  • Open Access


    Image Segmentation Based on Block Level and Hybrid Directional Local Extrema

    Ghanshyam Raghuwanshi1, Yogesh Gupta2, Deepak Sinwar1, Dilbag Singh3, Usman Tariq4, Muhammad Attique5, Kuntha Pin6, Yunyoung Nam7,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3939-3954, 2022, DOI:10.32604/cmc.2022.018423

    Abstract In the recent decade, the digitalization of various tasks has added great flexibility to human lifestyle and has changed daily routine activities of communities. Image segmentation is a key step in digitalization. Segmentation plays a key role in almost all areas of image processing, and various approaches have been proposed for image segmentation. In this paper, a novel approach is proposed for image segmentation using a nonuniform adaptive strategy. Region-based image segmentation along with a directional binary pattern generated a better segmented image. An adaptive mask of 8 × 8 was circulated over the pixels whose bit value was 1 in the… More >

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