Abstract: Support vector machines are an effect tool of data classification and regression, and there are widespread applications, such as image classification, image retrieval, face authentication, data analysis prediction and so on. In this paper, a novel image tamper detection based on support vector machines will be proposed and the tampering types will be discussed. First, we cut the protected image into several non-overlapping 8 by 8 blocks and retrieve three sets of feature values from each block, which contain ten maximal and minimal pixels and the sub-band LL coefficients after one-level discrete wavelet transformation. Next, we start to process the image with white and black tampering and obtain the feature value from the tampered image. Lastly, we use the retrieved image feature value to support vector machines` training, then the vector machines will produce a trained module, and this module can recognize and label all types of the tampered image.
Keh-Jian Ma , Tung-Shou Chen , Chun-Liang Tung and Chih-Wei Lin , 2004. Apply Support Vector Machines to the Tampered Images` Detection and Classification . Asian Journal of Information Technology, 3: 739-747.