A Fuzzy Based Clustering for Image Steganalysis
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Steganalysis is the technique for attacking steganography methods to detect the secret message. Image steganalysis can be viewed as a two class classification problem. To this end, this book has two contributions. First, to define grayscale image steganalysis based on Fuzzy c-Means Clustering the objective of the formulated fuzzy problem is to construct two fuzzy clusters: cover image and stego image clusters. The second contribution is to use Histogram Characteristic Function (HCF) and calibrated HCF by downsampling detectors and propose a new detector called calibrated HCF by Haar wavelet. T...
Steganalysis is the technique for attacking steganography methods to detect the secret message. Image steganalysis can be viewed as a two class classification problem. To this end, this book has two contributions. First, to define grayscale image steganalysis based on Fuzzy c-Means Clustering the objective of the formulated fuzzy problem is to construct two fuzzy clusters: cover image and stego image clusters. The second contribution is to use Histogram Characteristic Function (HCF) and calibrated HCF by downsampling detectors and propose a new detector called calibrated HCF by Haar wavelet. These detectors are exploited by the fuzzy clustering algorithm, as two feature set parameters, the first parameter is the first order moment (i.e. center of mass) and the second parameter is the first three moments to define the boundaries of the cover and stego image clusters.
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