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Although Synthetic Aperture Radar (SAR) can capture rich land cover information as a most important advanced technique in the field of international earth observation, the application effects still limited significantly. One of the reasons is that the study of SAR imaging processing, SAR image processing and SAR applications are usually conducted respectively, and the study on integrating the three...
Face diagnosis is one of the four diagnostic methods in Traditional chinese medicine (TCM). The morbidity of the organs can be revealed from the facial complexion. Due to the ambiguity of face diagnosis in TCM, Fuzzy support vector machine (FSVM) is utilized to remove the influence of outliers. The facial complexion recognition in TCM based on FSVM is proposed in this paper, which includes the following...
For improving the detection efficiency of hidden information blind detection system, an improved hidden information detection method based rough set theory is proposed against the high dimension of statistical features and high relevance about images. First, an improved general steganalysis system framework is proposed with practical method and steps; second, the Algorithm based on the rough set theory...
In this paper, a blind steganalytic scheme is proposed to effectively detect JPEG steganography. Nine statistical models are constructed from the DCT and decompressed spatial domain for a JPEG image. By calculating the histogram characteristic function (HCF) and the center of mass (COM), we measure the energy distribution of each model as one part of our feature set. Moreover, for each model constructed...
The goal of blind steganalysis is to detect the presence of hidden data and to eventually extract them from the stego images generated by various data hiding schemes. In this paper, we construct a new blind classifier capable of detecting several steganographies for JPEG images. Thirteen statistics are collected in the DCT domain and spatial domain. By using the characteristic function and the center...
Binary hyper-sphere support vector machine (SVM) is a new method for data description. Its weakness is that the margin between two classes of samples is zero or an uncertain value, which affects the classifier's generalization performance to some extent. So a generalized hyper-sphere SVM (GHSSVM) is provided in this paper. By introducing the parameter n and b (n>b), the margin which is greater...
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