Image Forgery Detection using Hash Functions
Sruthi S Menon1, Mary Saana N J2, Deepa G3
1Sruthi S Menon, Department of Computer Science and IT, Amrita Vishwa Vidyapeetham University/ Amrita School of Arts and Sciences Kochi, India.
2Mary Saana N J, Department of Computer Science and IT, Amrita Vishwa Vidyapeetham University/ Amrita School of Arts and Sciences Kochi, India.
3Deepa Gopinath, Department of Computer Science and IT, Amrita Vishwa University/ Amrita School of Artsand Sciences Kochi, India.
Manuscript received on 01 April 2019 | Revised Manuscript received on 06 May 2019 | Manuscript published on 30 May 2019 | PP: 3498-3501 | Volume-8 Issue-1, May 2019 | Retrieval Number: F2592037619 /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: Digital images are widely spread in today’s world and morphing of these images are also increased. Morphing of the images is the process of changing original image into another image using different tools. In social media the invasion of these morphed images are rapidly increasing and traditionally, the tampered images were found by the pixel comparison method. This way of detection leads to complexity and space consumption. pHash is used in this system as hashing algorithm.We effectively proposing a new and sophisticated technique to find morphed images using the features of pHash algorithm.
Index Terms: Image Forging, p (Perceptual Hash) Hash, Retouching, Splicing, Cloning, Hexalisation, Comparison, Grayscale Conversion.
Scope of the Article: Image Security