Digital images can be obtained through a variety of sources including digital cameras. With rapidly increasing functionality and ease of use of image editing software, determining authenticity and identifying forged regions, if any, is becoming crucial for many applications. This paper presents methods for authenticating and identifying forged regions in digital photo images that have been acquired. Our reexamination of some of these recently successful experiments shows that variations in image clarity in the experimental datasets were correlated with authenticity, and may have acted as a confounding factor, artificially improving the results. To determine the extent of this factor’s influence on previous results. We demonstrate that a feature derived from Hidden-Markov-Tree-modeling of the digital photo image forgery using wavelet coefficients has the potential to distinguish copies from originals in the new dataset.
INTRODUCTION
Digital image forgery is the process of manipulating photographic images using image-processing tools like digital photo editing software to produce a digital image as evidence to the court; there is a need to identify the authenticity of the image. Digital Image forgery can be classified as the forgery with copy move and without copy move.
More >> Detection of digital photo image forgery
No comments:
Post a Comment