Image Splicing Detection based on Surf with Ripplet Transform-ii
A. Jeyalakshmi1, D. Ramya Chitra2
1A. Jeyalakshmi, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Art and Science, Coimbatore (Tamil Nadu), India.
2Dr. D. Ramya Chitra, Assistant Professor, Department of Computer Science, Bharathiar University, Coimbatore (Tamil Nadu), India.
Manuscript received on 08 February 2019 | Revised Manuscript received on 14 February 2019 | Manuscript Published on 19 February 2019 | PP: 453-456 | Volume-7 Issue-5S January 2019 | Retrieval Number: ES2183017519/19©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: With the increasing popularity of digital devices, human being’s get collaged with the usage of digital devices and images in their daily life. Hence, Crimes also increased in many forms. Nowadays image splicing, image forgery is becoming a common way; the anti-social people are using to create the fake photographs and misusing them. So many researchers have already been carried out on image splicing. But the existing methods of detecting image splicing undergo the following challenge: original image is essential for revealing tampering. In this paper, we propose an efficient method to detect image splicing. In which, Ripplet-II transform based scheme outperforms for feature extraction in representing edges and textures of an image; also SURF is good at handling images with blurring and rotation.
Keywords: Image Splicing, Forgery Detection, SURF, Ripplet Transform-II.
Scope of the Article: Image Security