STM Journals Peer-reviewed research from Consortium e-Learning Network

Journal of Telecommunication, Switching Systems and Networks

Signature Forgery Detection using Python

  1. Deepya Yennamanen
  2. K Joseph Thanusha
  3. Dedeepya Padakanti

Abstract

Visual representation of information has become increasingly significant in the digital computing environment. Advancements in computer and network technologies have led to a rise in the accessibility and transmission of digital images through imaging technologies like digital cameras and scanners. Any manipulation of digital images that involves copying one part of the image into another part is considered a picture forgery. It is crucial to research methods to verify the integrity of images and detect tampering without prior knowledge of the image content or any embedded signatures. Recent developments in the field of digital image forgery detection are surveyed, and blind methods for forgery detection are presented in full bibliography. The article categorizes different methods of detecting image forgery and proposes a generalized structure. The current status of image forgery detection techniques is discussed, along with suggestions for future studies. There is an urgent need for automated tools capable of detecting false multimedia content and preventing the spread of dangerous false information.

Keywords

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