Who Recognized Fake Image Better: A Comparison Study between Human and Computer

International Conference on Computing and Applied Informatics 2016

物理学;计算机科学

Bahana, R.^1 ; Nurhudatiana, A.^2 ; Hidajat, M.^1 ; Budiono, T.A.^1

Computer Science Program, Bina Nusantara University, Jakarta, Indonesia^1

Information Systems Program, Bina Nusantara University, Jakarta, Indonesia^2

关键词: Alternative solutions;    Analysis approach;    Common practices;    Comparison study;    Desktop applications;    High-level features;    Image analysis method;    Prototype system;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/801/1/012042/pdf
DOI  :  10.1088/1742-6596/801/1/012042

学科分类：计算机科学（综合）

来源: IOP

【 摘 要 】

Along with the rapid development of multimedia and information technology in the recent years, a large number of photos and videos can be easily created and distributed by each and every member of our society. Some of these images are genuine, while some others have gone through modifications. Although the creation and posting of edited photographs in media are basically not prohibited, it becomes a problem when they are used improperly. Until now, the common practice in Indonesia when assessing whether an image has been modified or is original is still heavily dependent on human expert assessment that could be subjective. This research offers an alternative solution that is objective by developing a systematic image analysis method for distinguishing between original and modified image. The method utilizes high-level feature, namely the metadata of the image file, to differentiate between original and modified image. A prototype system was implemented in Visual Basic as a desktop application. The application used MS Windows GDI+. This prototype application can be used as a reliable and faster means to assist in fake image detection. However, as metadata-based analysis only detects whether a photograph has possibly been edited and it does not show which part of the photograph has been manipulated, future work includes development of pixel-based analysis approach.