Two-dimensional statistical test for the presence of almost cyclostationarity on images

Vazquez-Padin, David; Mosquera, Carlos; Pérez-González, Fernando

doi:10.1109/icip.2010.5652513

Cited by 29 publications

(28 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bi-dimensional cyclostationarity [120, Section 20] has been exploited in the following subjects: statistical test for the presence of almost cyclostationarity in images [352], sea clutter texture estimation [1], image forensic [24,234], and filtering and prediction [88,89].…”

Section: Miscellaneousmentioning

confidence: 99%

Cyclostationarity: New trends and applications

Napolitano

2016

Signal Processing

188

View full text Add to dashboard Cite

Section: Miscellaneousmentioning

confidence: 99%

Cyclostationarity: New trends and applications

Napolitano

2016

Signal Processing

188

View full text Add to dashboard Cite

“…The process of image rotation is often accompanied by an interpolation operation, which makes the cyclic spectral amplitude of covariance (second-order statistic) show a certain periodicity [3,9,10]. Assuming the original image is f (x 1 , x 2 ), the rotated image is as follows:…”

Section: Image Cyclic Spectrum and Its Rotation Theory Trajectorymentioning

confidence: 99%

“…Vazquez-Padin et al[9] applied a second-order cyclostationary method to detect the periodicity caused by resampling. Chen et al [3,10] improved the theoretical derivation and experimental results of Vazquez-Padin et al [9], and the further derivation of double resampling was presented. However, it resulted in larger errors when the rotation angle was small.…”

mentioning

confidence: 99%

Rotation Angle Estimation of JPEG Compressed Image by Cyclic Spectrum Analysis

et al. 2019

View full text Add to dashboard Cite

Image rotation is a common auxiliary method of image tampering, which can make the forged image more realistic from the geometric perspective. Most algorithms of image rotation angle estimation employ the peak value on the Fourier spectrum; however, JPEG post-processing brings additional peak interferences to the spectrum, which has a great impact on algorithm performance. In this paper, angle estimation is carried out for images compressed by JPEG. Firstly, the Fourier cyclic spectrum of image covariance is calculated, followed by semi-soft threshold wavelet transform to eliminate the block artefacts brought by JPEG compression. According to the shortest distance principle in the range of the limited amplitude, the processed cyclic spectral data are sorted to select the peak points. Finally, according to the selected peak point, the corresponding position coordinates of the theoretical peak point are found, and the rotation angle of the image is estimated by the theoretical peak point. Experimental results demonstrate that the average absolute error of the proposed algorithm is significantly lower than that of the state-of-the-art methods investigated, which highlights the promising potential of the proposed method as an image resampling detector in practical forensics applications.algorithm. In general, the EM algorithm can only judge whether the image was resampled or not, but it cannot estimate the resampling factor quantitatively. Furthermore, depending on the periodicity of the interpolation signal and its derivative, Mahdian et al. [6] introduced Radon transform to analyze the change in covariance statistics and detect the rotation angle of an image. The Radon transform algorithm can only judge the rotation operation of the image qualitatively, but it cannot estimate the concrete rotation angle. In order to solve the problem of the above algorithm not being able to estimate the resampling factor, Gallagher et al. [7] estimated the scaling factors of images based on the fact that interpolation signals (linear and cubic interpolation) would introduce periodicity to the second derivative on variance. However, the defect of this algorithm lies in the inaccurate estimation of the image scaling factor and the inability to detect down-sampling operations. To avoid this problem, Wei et al. [8] improved Gallagher's algorithm, derived a detection formula for image down-sampling, and proposed a method to estimate rotation angle. However, the method was only limited to the detection of single resampling, and no rigorous theoretical proof was given for the formula of peak position. Vazquez-Padin et al.[9] applied a second-order cyclostationary method to detect the periodicity caused by resampling. Chen et al. [3,10] improved the theoretical derivation and experimental results of Vazquez-Padin et al. [9], and the further derivation of double resampling was presented. However, it resulted in larger errors when the rotation angle was small. Reference [11] exposed the resampling traces by increasing the gap between image a...

show abstract

“…The proposed techniques in [4][5][6][7][8] work remarkably well when uncompressed signals are used, but the corresponding detectors can be easily deluded when a post-processing or simply a lossy-compression is applied to their content, as it is described in [9]. Furthermore, all these approaches are based on the study of the periodic correlation that is inherently induced in the resulting signals after applying a resampling operation.…”

Section: Introductionmentioning

confidence: 99%

“…One of the widely known methodologies to detect forgeries on multimedia contents consists in the analysis of the resam- piing factor of small portions across the whole content, which should be constant if no manipulation has been performed [4][5][6][7][8]. For instance, when an image splicing is carried out, it is very likely that one of the pasted regions has been transformed geometrically to adapt the content to the scene, thus introducing an inconsistency on the resampling factor in that part of the image.…”

Section: Introductionmentioning

confidence: 99%

Set-membership identification of resampled signals

Vazquez-Padin

Comesaña

Pérez-González

2013

2013 IEEE International Workshop on Information Forensics and Security (WIFS)

Self Cite

View full text Add to dashboard Cite

The problem o f resampling factor estimation as a means for tampering detection has been largely investigated. Most of the existing techniques rely on the analysis of cyclic correlations induced in the resampled signal. However, in this paper, a new direction is explored by addressing the same problem in terms of the set-membership estimation theory. The proposed technique constructs a model of the problem using available a priori knowledge and in consonance with a finite number of observations that comes from the resampled signal under study. With this information, the proposed technique is able to provide an estimate of the resampling factor applied to the original signal and, if required, an estimate of such signal and an estimate of the interpolation filter. The performance in terms of accuracy and MSE of the proposed approach is evaluated and comparative results with state-of-the-art methods are reported.

show abstract

Two-dimensional statistical test for the presence of almost cyclostationarity on images

Cited by 29 publications

References 4 publications

Cyclostationarity: New trends and applications

Cyclostationarity: New trends and applications

Rotation Angle Estimation of JPEG Compressed Image by Cyclic Spectrum Analysis

Set-membership identification of resampled signals

Contact Info

Product

Resources

About