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  • Open Access


    Image Splicing Forgery Detection Using Feature-Based of Sonine Functions and Deep Features

    Ala’a R. Al-Shamasneh1, Rabha W. Ibrahim2,3,4,*

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 795-810, 2024, DOI:10.32604/cmc.2023.042755

    Abstract The growing prevalence of fake images on the Internet and social media makes image integrity verification a crucial research topic. One of the most popular methods for manipulating digital images is image splicing, which involves copying a specific area from one image and pasting it into another. Attempts were made to mitigate the effects of image splicing, which continues to be a significant research challenge. This study proposes a new splicing detection model, combining Sonine functions-derived convex-based features and deep features. Two stages make up the proposed method. The first step entails feature extraction, then… More >

  • Open Access


    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… More >

  • Open Access


    Deep Learning Based Image Forgery Detection Methods

    Liang Xiu-jian1,2,*, Sun He2

    Journal of Cyber Security, Vol.4, No.2, pp. 119-133, 2022, DOI:10.32604/jcs.2022.032915

    Abstract Increasingly advanced image processing technology has made digital image editing easier and easier. With image processing software at one’s fingertips, one can easily alter the content of an image, and the altered image is so realistic that it is illegible to the naked eye. These tampered images have posed a serious threat to personal privacy, social order, and national security. Therefore, detecting and locating tampered areas in images has important practical significance, and has become an important research topic in the field of multimedia information security. In recent years, deep learning technology has been widely… More >

  • Open Access


    Image Splicing Detection Based on Texture Features with Fractal Entropy

    Razi J. Al-Azawi1, Nadia M. G. Al-Saidi2, Hamid A. Jalab3,*, Rabha W. Ibrahim4, Dumitru Baleanu5,6,7

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3903-3915, 2021, DOI:10.32604/cmc.2021.020368

    Abstract Over the past years, image manipulation tools have become widely accessible and easier to use, which made the issue of image tampering far more severe. As a direct result to the development of sophisticated image-editing applications, it has become near impossible to recognize tampered images with naked eyes. Thus, to overcome this issue, computer techniques and algorithms have been developed to help with the identification of tampered images. Research on detection of tampered images still carries great challenges. In the present study, we particularly focus on image splicing forgery, a type of manipulation where a… More >

  • Open Access


    Splicing Image and Its Localization: A Survey

    Jinwei Wang1,*, Yangyang Li2

    Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 77-86, 2019, DOI:10.32604/jihpp.2019.07186

    Abstract With the rapid development of information technology, digital images have become an important medium for information transmission. However, manipulating images is becoming a common task with the powerful image editing tools and software, and people can tamper the images content without leaving any visible traces of splicing in order to gain personal goal. Images are easily spliced and distributed, and the situation will be a great threat to social security. The survey covers splicing image and its localization. The present status of splicing image localization approaches is discussed along with a recommendation for future research. More >

  • Open Access


    Improved Fully Convolutional Network for Digital Image Region Forgery Detection

    Jiwei Zhang1, Yueying Li2, Shaozhang Niu1,*, Zhiyi Cao1, Xinyi Wang1

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 287-303, 2019, DOI:10.32604/cmc.2019.05353

    Abstract With the rapid development of image editing techniques, the image splicing behavior, typically for those that involve copying a portion from one original image into another targeted image, has become one of the most prevalent challenges in our society. The existing algorithms relying on hand-crafted features can be used to detect image splicing but unfortunately lack precise location information of the tampered region. On the basis of changing the classifications of fully convolutional network (FCN), here we proposed an improved FCN that enables locating the spliced region. Specifically, we first insert the original images into… More >

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