Forensic Detection of Digital Image Tampering Using Statistical Analysis
| Main Authors: | Md. Zahurul Haque, Md. Mahedi Hasan |
|---|---|
| Format: | Article eJournal |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/4130383 |
Daftar Isi:
- Abstract- Today, with an increasing volume of images being captured across an ever expanding range of devices, digital images are now ubiquitous in modern life. In parallel to advances in technology, we have socially come to understand events in a far more visual way than ever before. Digital images are now primary source of information in a wide range of fields from entertainment to mass media, from medical diagnosis to criminal justice, and even national security. This dependence on digital images, however, has brought with it a whole new set of issues and challenges which were not as apparent before. Due to the availability and increasing sophistication of advanced photo-editing software, there is a rampant problem of digital forgeries, which has seriously debased the credibility of digital images as definite records of events. As a consequence, doctored images are now appeared with a growing frequency in different application fields often leaving no visual clues of having been tampered with. On the other hand, for this reason digital image forensics has emerged as a new research field that aims to reveal tampering operations in digital images and to verify images authenticity. One of the primary goals of digital image forensics is to identify images and image regions which have undergone some form of manipulation or alteration. Because of the ill-posed nature of this problem, no catchall method of detecting image forgeries exists. Instead, a number of techniques have been proposed to identify image alterations under a variety of scenarios. But each of these methods possess their own limitations. This paper presents a comprehensive overview of the state of the art in the area of digital image forensics. An efficient statistical technique have also been presented for detecting region duplication, one of the most common forgeries on digital image.