RESEARCH ARTICLE INTELLIGENCE

Articles Published 3 September 2024

High Resolution Image Forgery Identification And Detection Using Machine Learning

AUTHORS & AFFILIATIONS

Pallavi Kulakarni Department of Computer Science and Engineering (MCA) VTU CPGS Kalaburagi-585105, Karnataka, India. ORCID ↗
Bharati S. Pochal Assistant Professor, Department of Computer Science and Engineering (MCA), Visvesvaraya Technological University Kalaburagi, Karnataka, India ORCID ↗

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Keywords:

Discrete Wavelet Transform(DWT), Discrete Cosine Transform(DCT), CMFD Algorithm

Abstract

Now a days we are blindly trusting the authenticity of digital imagery so image forgery is expanding with High frequency. By manipulating the technology to conceal some important or critical information about the image, digital image fraud might be done. The detection of forgery in the image is required to maintain the integrity and authenticity of the image. Utilizing digital images has become simpler with the aid of picture editing software as a result of acclimating to modern life and technological advancements in photographic equipment. Consequently, it is essential to spot these image forging techniques in the photos. On the basis of object removal, object addition, and unexpected size adjustments in the image, the fake of an image can be detected.

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Published

03-09-2024

How to Cite

Pallavi Kulakarni, & Bharati S. Pochal. (2024). High Resolution Image Forgery Identification And Detection Using Machine Learning. Journal of Scientific Research and Technology, 2(9), 1–11. https://doi.org/10.61808/jsrt135
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