Robust Algorithm for Detection of Copy-Move Forgery in Digital Images Based on Ridgelet Transform

Image Region Duplication Forgery Detection Based on Angular Radial Partitioning and Harris Key-Points

“…In [15], the ridgelet transform of divided blocks was applied to extract features and compute Hu moments for these features to produce feature vectors. Euclidean distance of feature vectors is computed for similarity measure.…”

A Survey of Partition-Based Techniques for Copy-Move Forgery Detection

“…Ridgelet Transform-Based. In [ 32 ], the ridgelet transform is applied to each block and Hu moments obtained from the ridgelet transformed blocks are used to represent the block. The method is robust to JPEG compression.…”

“…Once the data is organized so as to reduce the complexity of the similarity check, the search of similar features is done using various similarity criteria amongst which can be mentioned the Euclidean distance [ 50 – 52 ]; the measure S = 1/(1 + dis) [ 32 , 44 ] where dis is a distance measured in the Euclidean space; the Hamming distance [ 35 ]; the Hausdorff distance [ 53 ]; the logical distance [ 30 ]; the correlation coefficient [ 17 , 42 ]; the phase-correlation [ 46 , 64 ]; the normalized cross-spectrum [ 36 , 71 ]; the local sensitive hashing [ 69 , 74 ]; the ratio of the absolute error and the minimum value of the two components [ 22 ]; the mean and variance of the difference vector diff (diff( u , v ) = ( u 1 − v 1 , u 2 − v 2 ,…, u n − v n ) where u = ( u 1 , u 2 ,…, u n ) and v = ( v 1 , v 2 ,…, v n )) [ 56 ]; the absolute value of each component of the difference vector combined with their partial sums [ 43 ]; the absolute value of each component of the difference vector combined with the ratio of these absolute values and the minimum of the corresponding feature vector components taken as absolute values [ 33 ]; the sum of absolute values of components of the difference vector [ 54 ]; the absolute value of the difference between their block numbers (position of the top-left corner point) [ 13 ]; and the element by element comparison [ 61 ].…”