Methodology for Evidence Reconstruction in Digital Image Forensics

Article ID

CSTGV9G2HC

Methodology for Evidence Reconstruction in Digital Image Forensics

Kalpana Manudhane
Kalpana Manudhane G.H. Riasoni College of Engineering & Management
Mr. M.M. Bartere
Mr. M.M. Bartere
DOI

Abstract

This paper reveals basics of Digital (Image) Forensics. The paper describes the ways to manipulate image, namely, copy-move forgery (copy region in image & paste into another region in same image), image splicing (copy region in image & paste into another image) and image retouching. The paper mainly focuses on copy move forgery detection methods that are classified mainly into two broad approaches- block-based and key-point. Methodology (generalized as well as approach specific) of copy move forgery detection is presented in detail. Copied region is not directly pasted but manipulated (scale, rotation, adding Gaussian noise or combining these transformations) before pasting. The method for detection should robust to these transformations. The paper also presents methodology for reconstruction (if possible) of forged image based on detection result.

Methodology for Evidence Reconstruction in Digital Image Forensics

This paper reveals basics of Digital (Image) Forensics. The paper describes the ways to manipulate image, namely, copy-move forgery (copy region in image & paste into another region in same image), image splicing (copy region in image & paste into another image) and image retouching. The paper mainly focuses on copy move forgery detection methods that are classified mainly into two broad approaches- block-based and key-point. Methodology (generalized as well as approach specific) of copy move forgery detection is presented in detail. Copied region is not directly pasted but manipulated (scale, rotation, adding Gaussian noise or combining these transformations) before pasting. The method for detection should robust to these transformations. The paper also presents methodology for reconstruction (if possible) of forged image based on detection result.

Kalpana Manudhane
Kalpana Manudhane G.H. Riasoni College of Engineering & Management
Mr. M.M. Bartere
Mr. M.M. Bartere

No Figures found in article.

Kalpana Manudhane. 2014. “. Global Journal of Computer Science and Technology – F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F9): .

Download Citation

Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Classification
Not Found
Article Matrices
Total Views: 8800
Total Downloads: 2397
2026 Trends
Research Identity (RIN)
Related Research
Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Methodology for Evidence Reconstruction in Digital Image Forensics

Kalpana Manudhane
Kalpana Manudhane G.H. Riasoni College of Engineering & Management
Mr. M.M. Bartere
Mr. M.M. Bartere

Research Journals