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Article Released Mon-3rd-July-2017 09:33 GMT
Contact: Dr Nayan KANWAL, FRSA, ABIM, AMIS, Ph.D. Institution: Universiti Putra Malaysia (UPM)
 Arsenal against fake images strengthened

A new approach could help detect forged parts of photographs faster and more accurately than current methods.

Image Name
Copy-move forgery is difficult to detect because it involves copying an object or an area in an image and using it in another part of the same image.
Copyright : Allan Swart / 123rf
Researchers at India’s Jaypee University of Information Technology have developed a new way to detect ‘copy-move forgery’ in photographs that is more successful and faster than currently available methods.

Copy-move forgery is difficult to detect because it involves copying an object or an area in an image and using it in another part of the same image. This is typically done to cover something up or to add something that was not previously there. For example, an image of three missiles can be forged to look like an image containing five, where two of the missiles are copied and added elsewhere in the picture. Forgers can also use this technique to hide critical data in a crime scene.

Copy-move forgery is difficult to detect because the altered parts of the photograph contain a similar palette, texture and distortions as the original image.

Currently available approaches to detect this type of forgery are slow, as they involve a large number of computational calculations. They can also give false positive results.

The researchers sped up the process by converting an image into its binary form, such that each pixel in the image is either black or white, with black representing parts of objects in the image and white representing the background.

The team developed an algorithm that then translates each black pixel in the image into a position on a histogram. Copied parts of an image will have the same ‘profile’ in the histogram as an original object in the image. This appears in the shape of a repeated ‘valley’ in the histogram. Other objects in the image will also appear as valleys, but they will not match the other valleys.

The team successfully tested their method on more than 20 forged images of various sizes and found that there is “tremendous improvement” in the computation time, especially for larger images, compared to other methods.

The technique is limited to images with distinct contrast between copied objects and the image background, according to the study published in the Pertanika Journal of Science & Technology.

For more information about this research, please contact:

Mohd Dilshad Ansari
Department of Computer Science and Engineering
Jaypee University of Information Technology
Waknaghat, Solan 1732 34, India
Email: m.dilshadcse@gmail.com
Mobile: +(91) 9816 387 077


About Pertanika Journal of Science & Technology (JST)
Pertanika Journal of Science & Technology (JST) is published by Universiti Putra Malaysia in English and is open to authors around the world regardless of nationality. Currently, it is published twice a year in January and July. Other Pertanika series include Pertanika Journal of Tropical Agricultural Science (JTAS), and Pertanika Journal of Social Sciences & Humanities (JSSH).

Pertanika Journal of Science & Technology aims to provide a forum for high quality research related to science and engineering research. Areas relevant to the scope of the journal include: bioinformatics, bioscience, biotechnology and bio-molecular sciences, chemistry, computer science, ecology, engineering, engineering design, environmental control and management, mathematics and statistics, medicine and health sciences, nanotechnology, physics, safety and emergency management, and related fields of study.

For more information about the journal, contact:

The Chief Executive Editor (UPM Journals)
Office of the Deputy Vice Chancellor (R&I)
IDEA Tower 2, UPM-MDTC Technology Centre
Universiti Putra Malaysia
43400 Serdang, Selangor
Malaysia.

Phone: +(603) 8947 1622 | +(6016) 217 4050
Email: nayan@upm.my



Date of Release: 03 July 2017.

Acknowledgements
The Chief Executive Editor, UPM Journals

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