CASIA Image Tampering Detection Evaluation Database

TLDR

Image forensics is increasingly important due to rising cases of tampered images used in media and court evidence. The paper aims to provide a realistic open benchmark database to verify image content authenticity and support passive‑blind tampering detection methods. The authors collected a natural color image database with realistic tampering operations, organized it as the CASIA Image Tampering Detection Evaluation Database, and described its design criteria and self‑evaluation. The database is publicly available for researchers to compare and evaluate tampering detection techniques.

Abstract

Image forensics has now raised the anxiety of justice as increasing cases of abusing tampered images in newspapers and court for evidence are reported recently. With the goal of verifying image content authenticity, passive-blind image tampering detection is called for. More realistic open benchmark databases are also needed to assist the techniques. Recently, we collect a natural color image database with realistic tampering operations. The database is made publicly available for researchers to compare and evaluate their proposed tampering detection techniques. We call this database CASI-A Image Tampering Detection Evaluation Database. We describe the purpose, the design criterion, the organization and self-evaluation of this database in this paper.