Histogram and Feature Encoding Based Fake Colorized Image Detection Using Machine Learning

EasyChair Preprint no. 6025

Abstract

Colorization is an emerging image editing technique, in which gray scale images are colorized with realistic colors. Till now, no forensic technique has been invented to detect whether an image is colorized. As compared to natural pictures, colorized images, are generated by three state-of-the-art methods, which possesses statistical differences for the hue and saturation channels. We also observe applied mathematics inconsistencies within the dark and bright channels. We propose detection methods for fake colorized images Histogram based Fake Colorized Image Detection and Feature Encoding based Fake Colorized Image Detection using Machine Learning.

Keyphrases: Fake Colorized Image Detection, Hue, Image forgery detection, saturation

@Booklet{EasyChair:6025,
  author = {Yogesh Gaikwad and Jaishree Waghmare},
  title = {Histogram and Feature Encoding Based Fake Colorized Image Detection Using Machine Learning},
  howpublished = {EasyChair Preprint no. 6025},

  year = {EasyChair, 2021}}