Camera Model Identification using Deep CNN and Transfer Learning Approach

被引：0

作者：

Al Banna, Md Hasan ^{[1
]}

Haider, Md Ali ^{[1
]}

Al Nahian, Md Jaber ^{[1
]}

Islam, Md Maynul ^{[1
]}

Abu Taher, Kazi ^{[1
]}

Kaiser, M. Shamim ^{[2
]}

机构：

[1] Bangladesh Univ Profess, Dept Informat & Commun Engn, Dhaka, Bangladesh

[2] Jahangirnagar Univ, Inst Informat Technol, Dhaka, Bangladesh

来源：

2019 1ST INTERNATIONAL CONFERENCE ON ROBOTICS, ELECTRICAL AND SIGNAL PROCESSING TECHNIQUES (ICREST) | 2019年

关键词：

image forensic; MobileNet; Deep CNN; Machine Learning; Classification;

D O I：

10.1109/icrest.2019.8644194

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The forensic investigation on digital images is to assess the authenticity of images without the embedded security on the images. The camera model identification is the first step for image forensic investigation. The paper proposes the deep Convolutional Neural Network and transfer learning approach for extracting features from an images dataset. An open image dataset of 3900 images have been created using three camera models. Three state-of-the-art machine learning algorithms such as SVM, logistic regression and random forest based classifiers have been used for evaluating identification accuracy.

引用

页码：626 / 630

页数：5

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