This paper is published in Volume-3, Issue-2, 2017
Area
Computer Science
Author
Er. Nisha, Er. Rajnish Kansal
Org/Univ
ACET Bhawanigarh, India, India
Pub. Date
25 March, 2017
Paper ID
V3I2-1258
Publisher
Keywords
Copy Move Forgery, SVM, ORB.

Citationsacebook

IEEE
Er. Nisha, Er. Rajnish Kansal. Classification of Copy Move Forgery and Normal Images By ORB Features And SVM Classifier, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Er. Nisha, Er. Rajnish Kansal (2017). Classification of Copy Move Forgery and Normal Images By ORB Features And SVM Classifier. International Journal of Advance Research, Ideas and Innovations in Technology, 3(2) www.IJARIIT.com.

MLA
Er. Nisha, Er. Rajnish Kansal. "Classification of Copy Move Forgery and Normal Images By ORB Features And SVM Classifier." International Journal of Advance Research, Ideas and Innovations in Technology 3.2 (2017). www.IJARIIT.com.

Abstract

the fact that the need for detection of digital forgeries has been recognized by the research community, very few publications are currently available. Digital watermarks have been proposed as a means for fragile authentication, content authentication, detection of tampering, localization of changes, and recovery of original content. While digital watermarks can provide useful information about the image integrity and its processing history, the watermark must be present in the image before the tampering occurs. This limits their application to controlled environments that include military systems or surveillance cameras. Unless all digital acquisition devices are equipped with a watermarking chip, it will be unlikely that a forgery-in the-wild will be detectable using a watermark. In this paper use COMFOD dataset by SVM with ORB features
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