Detection of Manipulated Images using Convolutional Neural Network
R. Sathya1, Abhijit Kumar Sanu2, Avinash Singh3, Saurav Chaurasia4, Vishal Agrawal5
1R. Sathya, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Abhijit Kumar Sanu, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3Avinash Singh, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4Saurav Chaurasia, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
5Vishal Agrawal, Department of Computer Science, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 18 April 2019 | Revised Manuscript received on 25 April 2019 | Manuscript published on 30 April 2019 | PP: 1431-1438 | Volume-8 Issue-4, April 2019 | Retrieval Number: D6155048419/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Now a days, photos are considered as critical part in different fields like computerized crime scene investigation, therapeutic imaging, logical productions, in the courts as a proof, and so forth. As the improvement in innovation is expanding step by step, in the meantime the trust in pictures is diminishing step by step. Most normal kind of Image phony is Image piece which is likewise named by the name Image Splicing. Mix of at least two pictures to create a totally phony picture is known as Image arrangement. It turns out to be difficult to separate between genuine picture and phony picture due to the nearness of different amazing altering programming. Accordingly, in a large portion of the cases, there is a need to demonstrate whether the picture is genuine or not.
Keywords: Manipulated Image Detection, Metadata Analysis, Neural Network, Hue, Saturation, Histogram.
Scope of the Article: Neural Information Processing