@inproceedings{11d246adae7c4d73af4d6fa1fee28d66,
title = "Blind image tamper detection based on multimodal fusion",
abstract = "In this paper, we propose a novel feature processing approach based on fusion of noise and quantization residue features for detecting tampering or forgery in video sequences. The evaluation of proposed residue features – the noise residue features and the quantization features, their transformation in optimal feature subspace based on fisher linear discriminant features and canonical correlation analysis features, and their subsequent fusion for emulated copy-move tamper scenarios shows a significant improvement in tamper detection accuracy.",
author = "Girija Chetty and Monica Singh and Matthew White",
year = "2010",
doi = "10.1007/978-3-642-17534-3_69",
language = "English",
series = "Lecture Notes in Computer Science ",
publisher = "Springer",
pages = "557--564",
editor = "Wong, {Kok Wai} and Mendis, {B. Sumudu U} and Abdesselam Bouzerdoum",
booktitle = "Lecture Notes in Computer Science: Neural Information Processing: Models and Application: 17th International Conference, ICONIP 2010 Sydney, Australia, November 22-25, 2010 Proceedings Part II",
address = "Netherlands",
note = "ICONIP 2010 - 17th International Conference on Neural Information Processing ; Conference date: 22-11-2010 Through 25-11-2010",
}