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Search Results (13)
  • Open Access

    ARTICLE

    An Active Image Forgery Detection Approach Based on Edge Detection

    Hüseyin Bilal Macit1, Arif Koyun2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1603-1619, 2023, DOI:10.32604/cmc.2023.036216

    Abstract Recently, digital images have become the most used data, thanks to high internet speed and high resolution, cheap and easily accessible digital cameras. We generate, transmit and store millions of images every second. Most of these images are insignificant images containing only personal information. However, in many fields such as banking, finance, public institutions, and educational institutions, the images of many valuable objects like ID cards, photographs, credit cards, and transaction receipts are stored and transmitted to the digital environment. These images are very significant and must be secured. A valuable image can be maliciously modified by an attacker. The… More >

  • Open Access

    ARTICLE

    Color Edge Detection Using Multidirectional Sobel Filter and Fuzzy Fusion

    Slim Ben Chaabane1,2,*, Anas Bushnag1

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2839-2852, 2023, DOI:10.32604/cmc.2023.032760

    Abstract A new model is proposed in this paper on color edge detection that uses the second derivative operators and data fusion mechanism. The second-order neighborhood shows the connection between the current pixel and the surroundings of this pixel. This connection is for each RGB component color of the input image. Once the image edges are detected for the three primary colors: red, green, and blue, these colors are merged using the combination rule. Then, the final decision is applied to obtain the segmentation. This process allows different data sources to be combined, which is essential to improve the image information… More >

  • Open Access

    ARTICLE

    Intelligent Machine Learning Enabled Retinal Blood Vessel Segmentation and Classification

    Nora Abdullah Alkhaldi1,*, Hanan T. Halawani2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 399-414, 2023, DOI:10.32604/cmc.2023.030872

    Abstract Automated segmentation of blood vessels in retinal fundus images is essential for medical image analysis. The segmentation of retinal vessels is assumed to be essential to the progress of the decision support system for initial analysis and treatment of retinal disease. This article develops a new Grasshopper Optimization with Fuzzy Edge Detection based Retinal Blood Vessel Segmentation and Classification (GOFED-RBVSC) model. The proposed GOFED-RBVSC model initially employs contrast enhancement process. Besides, GOAFED approach is employed to detect the edges in the retinal fundus images in which the use of GOA adjusts the membership functions. The ORB (Oriented FAST and Rotated… More >

  • Open Access

    ARTICLE

    Spoofing Face Detection Using Novel Edge-Net Autoencoder for Security

    Amal H. Alharbi1, S. Karthick2, K. Venkatachalam3, Mohamed Abouhawwash4,5, Doaa Sami Khafaga1,*

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2773-2787, 2023, DOI:10.32604/iasc.2023.030763

    Abstract Recent security applications in mobile technologies and computer systems use face recognition for high-end security. Despite numerous security techniques, face recognition is considered a high-security control. Developers fuse and carry out face identification as an access authority into these applications. Still, face identification authentication is sensitive to attacks with a 2-D photo image or captured video to access the system as an authorized user. In the existing spoofing detection algorithm, there was some loss in the recreation of images. This research proposes an unobtrusive technique to detect face spoofing attacks that apply a single frame of the sequenced set of… More >

  • Open Access

    ARTICLE

    An Image Edge Detection Algorithm Based on Multi-Feature Fusion

    Zhenzhou Wang1, Kangyang Li1, Xiang Wang1,*, Antonio Lee2

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4995-5009, 2022, DOI:10.32604/cmc.2022.029650

    Abstract Edge detection is one of the core steps of image processing and computer vision. Accurate and fine image edge will make further target detection and semantic segmentation more effective. Holistically-Nested edge detection (HED) edge detection network has been proved to be a deep-learning network with better performance for edge detection. However, it is found that when the HED network is used in overlapping complex multi-edge scenarios for automatic object identification. There will be detected edge incomplete, not smooth and other problems. To solve these problems, an image edge detection algorithm based on improved HED and feature fusion is proposed. On… More >

  • Open Access

    ARTICLE

    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

    ARTICLE

    Community Detection Using Jaacard Similarity with SIM-Edge Detection Techniques

    K. Chitra*, A. Tamilarasi

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 327-337, 2023, DOI:10.32604/csse.2023.023920

    Abstract The structure and dynamic nature of real-world networks can be revealed by communities that help in promotion of recommendation systems. Social Media platforms were initially developed for effective communication, but now it is being used widely for extending and to obtain profit among business community. The numerous data generated through these platforms are utilized by many companies that make a huge profit out of it. A giant network of people in social media is grouped together based on their similar properties to form a community. Community detection is recent topic among the research community due to the increase usage of… More >

  • Open Access

    ARTICLE

    Smart Garbage Bin Based on AIoT

    Wen-Tsai Sung1, Ihzany Vilia Devi1, Sung-Jung Hsiao2,*, Fathria Nurul Fadillah1

    Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1387-1401, 2022, DOI:10.32604/iasc.2022.022828

    Abstract Waste management and monitoring is a major concern in the context of the environment, and has a significant impact on human health. The concept of the Artificial Intelligence of Things (AIoT) can help people in everyday tasks in life. This study proposes a smart trash bin to help solve the problem of waste management and monitoring. Traditional methods of garbage disposal require human labor, and pose a hazard to the worker. The proposed smart garbage bin can move itself by using ultrasonic sensors and a web camera, which serves as its “eyes.” Because the smart garbage bin is designed for… More >

  • Open Access

    ARTICLE

    Canny Edge Detection Model in MRI Image Segmentation Using Optimized Parameter Tuning Method

    Meera Radhakrishnan1,*, Anandan Panneerselvam2, Nandhagopal Nachimuthu3

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1185-1199, 2020, DOI:10.32604/iasc.2020.012069

    Abstract Image segmentation is a crucial stage in the investigation of medical images and is predominantly implemented in various medical applications. In the case of investigating MRI brain images, the image segmentation is mainly employed to measure and visualize the anatomic structure of the brain that underwent modifications to delineate the regions. At present, distinct segmentation approaches with various degrees of accurateness and complexities are available. But, it needs tuning of various parameters to obtain optimal results. The tuning of parameters can be considered as an optimization issue using a similarity function in solution space. This paper presents a new Parametric… More >

  • Open Access

    ARTICLE

    Enhanced GPU-Based Anti-Noise Hybrid Edge Detection Method

    Sa’ed Abed, Mohammed H. Ali, Mohammad Al-Shayeji

    Computer Systems Science and Engineering, Vol.35, No.1, pp. 21-37, 2020, DOI:10.32604/csse.2020.35.021

    Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically. Thus, increased processing power is… More >

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