Normalized Energy Density-Based Forensic Detection of Resampled Images


We propose a new method to detect resampled imagery. The method is based on examining the normalized energy density present within windows of varying size in the second derivative of the image in the frequency domain, and exploiting this characteristic to derive a 19-D feature vector that is used to train a SVM classifier. Experimental results are reported on 7500 raw images from the BOSS database. Comparison with prior work reveals that the proposed algorithm performs similarly for resampling rates greater than 1, and is superior to prior work for resampling rates less than 1. Experiments are performed for both bilinear and bicubic interpolations, and qualitatively similar results are observed for each. Results are also provided for the detection of resampled imagery with noise corruption and JPEG compression. As expected, some degradation in performance is observed as the noise increases or the JPEG quality factor declines.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Shape Based Normalized Cuts Using Spectral Relaxation for Biomedical Segmentation - 2014 ABSTRACT: We have a tendency to present a novel technique to incorporate previous knowledge into normalized cuts. The
PROJECT TITLE :Normalized Subband Adaptive Filtering Algorithm With Reduced Computational ComplexityABSTRACT:Subband structures are appropriate for improving convergence properties of adaptive filtering algorithms, notably for
PROJECT TITLE :Piecewise Normalized Normal Constraint Method Applied to Minimization of Voltage Deviation and Active Power Loss in an AC–DC Hybrid Power SystemABSTRACT:During this paper, we establish a mathematical model of
PROJECT TITLE :Determination of Normalized Magnetic Eigenfields in Microwave CavitiesABSTRACT:The magnetic field integral equation for axially symmetric cavities with perfectly conducting surfaces is discretized in step with a
PROJECT TITLE :On Convergence of Proportionate-Type Normalized Least Mean Square AlgorithmsABSTRACT:During this paper, a new convergence analysis is presented for a widely known sparse adaptive filter family, particularly, the

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry