We investigate the prospect of using bicoherence features for blind image splicing detection. Image splicing is an essential operation for digital photomontaging, which in turn is a technique for creating image forgery. We examine the properties of bicoherence features on a data set, which contains image blocks of diverse image properties. We then demonstrate the limitation of the baseline bicoherence features for image splicing detection. Our investigation has led to two suggestions for improving the performance of bicoherence features, i.e., estimating the bicoherence features of the authentic counterpart and incorporating features that characterize the variance of the feature performance. The features derived from the suggestions are evaluated with support vector machine (SVM) classification and is shown to improve the image splicing detection accuracy from 62% to about 70%.

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Blind detection of photomontage using higher order statistics

Signal processing techniques applied to human sleep EEG signals - a review

Third-order spectral techniques for the diagnosis of motor bearing condition using artificial neural networks

A future possibility of vibration based condition monitoring of rotating machines

This paper describes a global non-destructive testing technique for detecting fatigue cracking in engineering components. The technique measures the mixing of two ultrasonic sinusoidal waves which are excited by a small piezoceramic disc bonded to the test structure. This input signal excites very high-order modes of vibration of the test structure within the ultrasonic frequency range. The response of the structure is measured by a second piezoceramic disc and the received waveform is analysed using the bispectrum signal processing technique. Frequency mixing occurs as a result of nonlinearities within the test structure and fatigue cracking is shown to produce a strong mixing effect. The bispectrum is shown to be particularly suitable for this application due to its known insensitivity to noise. Experimental results on steel beams are used to show that fatigue cracks, corresponding to a reduction in the beam section of 8%, can be detected. It is also shown that the bispectrum can be used to quantify the extent of the cracking. A simple nonlinear spring model is used to interpret the results and demonstrate the robustness of the bispectrum for this application.

/pdf/global-crack-detection-using-bispectral-analysis-xjv55w4u4c.pdf

J. W. A. Fackrell

Papers

The interpretation of the bispectra of vibration signals—: I. Theory

The interpretation of the bispectra of vibration signals—: II. Experimental results and applications

Proceedings of the 8th European Signal Processing Conference (EUSIPCO)