Seam Carving Detection Using Convolutional Neural Networks

被引：0

作者：

da Silva Cieslak, Luiz Fernando ^{[1
]}

Pontara da Costa, Kelton Augusto ^{[1
]}

Papa, Joao Paulo ^{[1
]}

机构：

[1] Sao Paulo State Univ, UNESP, BR-17033360 Bauru, SP, Brazil

来源：

2018 IEEE 12TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI) | 2018年

基金：

巴西圣保罗研究基金会;

关键词：

Deep Learning; Convolutional Neural Networks; Seam Carving; Computer Forensics;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Deep Learning techniques have been widely used in the recent years, primarily because of their efficiency in several applications, such as engineering, medicine, and data security. Seam carving is a content-aware image resizing method that can also be used for image tampering, being not straightforward to be identified. In this paper, we combine Convolutional Neural Networks and Local Binary Patterns to recognize whether an image has been modified automatically or not by seam carving. The experimental results show that the proposed approach can achieve accuracies within the range [81% - 98%] depending on the severity of the tampering procedure.

引用

页码：195 / 199

页数：5

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