Image forgery detection using image similarity
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Image forgery detection using image similarity Saif alZahir 1
& Radwa Hammad
2
Received: 7 January 2020 / Revised: 20 July 2020 / Accepted: 29 July 2020 # Crown 2020
Abstract
Ideally, sophisticated image forgery methods leave no perceptible evidence of tampering. In response to such stringent context, researchers have proposed digital methods to detect such indiscernible tampering. In this paper, we present a blind image forgery detection method that uses a steerable pyramid decomposition technique and copulas ensemble. This method can accurately detect forgery in regions as small as 16 pixels, which is the smallest size reported in the literature with perfect accuracy. The proposed method is innovative in that: (i) it works on both grey scale images as well as colored images; (ii) the copula functions are used to calculate image similarity (or dissimilarity) which represents image forgery; (iii) the precision of the copula results on the image steerable pyramid bands motivated the idea of selecting the band with minimum number of elements to represent the block(s) in the image, which is 16 elements, in our case. The idea of using smallest number of elements to represent the blocks can significantly speed up the method as the testing is done on such small number of pixels; finally (iv) this method can be applied to more than one kind of image forgery with similar results. To verify the performance of the proposed method, we tested it on the well-known Copy Move Forgery Detection database (CoMoFoD) using 5123 image variations of the database. Also, we compared our results with five previously published algorithms and found that the proposed method outperformed those algorithms even when the forged images were subjected to postprocessing manipulations and transformations. Keywords Copula . Blind imageforgery detection . Image quality measures . Mutual information . Human visual system . Steerable pyramid
* Saif alZahir [email protected]; [email protected] Radwa Hammad [email protected]
1
ECE Department, Concordia University, 1455 De Maisonneuve Blvd. W. EV 5.139, Montreal, QC H3G 1M8, Canada
2
Computer Science Department, UNBC, Prince George, BC, Canada
Multimedia Tools and Applications
1 Introduction Image forgery detection methods are substantially used in a wide range of image processing applications including compression, recognition, classification, transformation, transmission, and retrieval [2, 5, 26]. Few decades ago, it was very difficult to manipulate images captured by basic or standard cameras due to the necessary professional knowledge and complicated darkrooms gear. Nowadays, the wide spread of image manipulation software and tools made it so easy to create fake images even by a person with little knowledge of photography [2, 26, 27]. Such increased occurrence of image forgery created an urgent need to develop techniques that are capable of verifying and authenticating digital original images. These techniques are very essential as their output can be presented as evidence in a court
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