ISD-SSD: image splicing detection by using modified single shot MultiBox detector

Yongxin Xue; Chen Zhu; Xiangqiong Tan

doi:10.1117/12.2659381

30 November 2022 ISD-SSD: image splicing detection by using modified single shot MultiBox detector

Yongxin Xue, Chen Zhu, Xiangqiong Tan

Proceedings Volume 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022); 124562J (2022) https://doi.org/10.1117/12.2659381
Event: International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 2022, Qingdao, China

Abstract

Detecting image splicing has become essential to fight against malicious forgery. To solve the problems of low accuracy of authenticity classification and low detection efficiency in some image splicing detection methods proposed in recent years, we propose an image splicing forgery detection method based on modified SSD network (ISD-SSD). In this method, the residual network model ResNet-50 is used to replace the feature extraction backbone network VGG-16 in SSD, which solves the problem of degradation caused by the deepening of the network and enhances the feature extraction ability of the model. In the multi-scale detection part, a multi-scale feature fusion module is introduced based on the feature pyramid idea, which organically combines the low-level visual features and high-level semantic features in the network structure. Finally, Focal loss is selected as the loss function in the loss calculation part to solve the problem of positive and negative samples and the imbalance of difficult and easy samples. Experiments on standard image manipulation datasets demonstrate that our ISD-SSD algorithm is superior to the existing image tamper detection algorithms (such as MFCN, Faster R-CNN algorithm, etc.), the evaluation metrics AP and F1 reach 77.86% and 75.18% respectively. In addition, it shows robustness in terms of detection speed.

Citation Download Citation

Yongxin Xue, Chen Zhu, and Xiangqiong Tan "ISD-SSD: image splicing detection by using modified single shot MultiBox detector", Proc. SPIE 12456, International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), 124562J (30 November 2022); https://doi.org/10.1117/12.2659381

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

RGB color model

Detection and tracking algorithms

Image fusion

Feature extraction

Performance modeling

Convolution

Modulation

Show All Keywords

Keywords/Phrases

Search In:

Publication Years