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Summary
This summary is machine-generated.

This study introduces a novel digital image authentication method to combat undetectable photo tampering. The technique combines texture analysis, discrete wavelet transform, and discrete cosine transform for reliable image verification.

Keywords:
digital imagesdiscrete cosine transformsforgery detectionimage forensicsimages splicinglocal pattern binarysupport vector machineswavelet transforms

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Area of Science:

  • Computer Science
  • Digital Forensics
  • Image Processing

Background:

  • Rapid proliferation of digital images and editing tools compromises authenticity.
  • Internet facilitates easy distribution, leading to uncritical acceptance of visual information.
  • Need for robust digital image authentication techniques is critical.

Purpose of the Study:

  • To propose and evaluate a novel digital image authentication technique.
  • To address the challenge of undetectable image tampering.
  • To enhance the veracity of digital images in modern society.

Main Methods:

  • Feature extraction using local texture patterns, Discrete Wavelet Transform (DWT), and Discrete Cosine Transform (DCT).
  • Development of an image authenticity verification model using a Support Vector Machine (SVM).
  • Testing the method on falsified images from established public databases.

Main Results:

  • The proposed method effectively detects tampered digital images.
  • Experimental results demonstrate high efficiency in authenticating image integrity.
  • The technique successfully identifies modifications without visible traces.

Conclusions:

  • The combined approach of texture analysis and transform domains offers a robust solution for digital image authentication.
  • The developed SVM model provides reliable verification of image authenticity.
  • This technique is crucial for maintaining trust in digital visual media.