Structural Correlation Based Method for Image Forgery Classification and Localization

Autor: Nam Thanh Pham, Jong-Weon Lee, Chun-Su Park
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Applied Sciences, Vol 10, Iss 13, p 4458 (2020)
Druh dokumentu: article
ISSN: 2076-3417
DOI: 10.3390/app10134458
Popis: In the image forgery problems, previous works has been chiefly designed considering only one of two forgery types: copy-move and splicing. In this paper, we propose a scheme to handle both copy-move and splicing image forgery by concurrently classifying the image forgery types and localizing the forged regions. The structural correlations between images are employed in the forgery clustering algorithm to assemble relevant images into clusters. Then, we search for the matching of image regions inside each cluster to classify and localize tampered images. Comprehensive experiments are conducted on three datasets (MICC-600, GRIP, and CASIA 2) to demonstrate the better performance in forgery classification and localization of the proposed method in comparison with state-of-the-art methods. Further, in copy-move localization, the source and target regions are explicitly specified.
Databáze: Directory of Open Access Journals