International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 08 Issue: 11 | Nov 2021
p-ISSN: 2395-0072
www.irjet.net
differs as the image contains regions having different print patterns. These patterns can be identified by a study of variogram generated for an image. 4.1. Window-wise analysis of variogram Variogram [19], [20], [21] is a statistical tool that characterizes spatial continuity or roughness of data set. It gives an average dissimilarity between points separated by distance h in specific direction d. Variogram is calculated as shown in Equation 1. The separation distance h is usually referred to as lag. Vd(h) =
f(xi + hd) − f(xi))2 ---------- Eq(1)
where Vd(h) is the variance in the direction d with lag h. Maximum variance in variogram is referred as sill and even at zero distance or lag there is some variability which results in nugget effect. Range represents the distance at which variables have no correlation. The plot of lag h versus V(h) provides graphical representation of variogram. Directional dependence of data present in the image is visualized by employing directional content in variogram concept. Window wise analysis involves moving fixed size window over tampered image for generating variograms and comparing them to inspect any dissimilarities. For example, variograms generated for homogeneous regions of genuine(Deskjet930c) image and tampered image shows an increasing variance of tampered image and as shown in Fig. 4. The increase in the variance of the tampered image has been observed but this does not reveal whether the image has been tampered or not. If it is a tampered image then we need to identify the tampered regions. By generating variogram for fixed size non-overlapping windows of sample[22], it is possible to interpret the distinguishable features in the sample which do not belong to the original image. The proposed method of window wise analysis of variogram assists a document examiner in interpreting the altered parts of the document which contains pictures or images. The steps for identifying tampered regions in uniform colour region are explained in Algorithm 1.
Fig- 4:. Variograms of Deskjet image and tampered image 4.2. Algorithm for identification of tampered part of the document Algorithm 1 Algorithm for identification of tampered part of the document findtamperregions(sample,d) Input: Sample image of size M by M d is direction in angle 1: [V, S, A nugget, Range] = variogram(sample, d) //Fix window size say R 2: R ≥ Range and R ≥ M/4 //Fix Number of windows say N 3: N= square(floor(M/R) //Where M=size of the sample 4: for i = 1 to N do © 2021, IRJET
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