Image Tampering Detection for Splicing based on Rich Feature and Convolution Neural Network
Tongfeng Yang, Jian Wu, Fang Zhifeng · 2020
Image splicing is a widely used image tampering method. The detection of these methods has also been widely concerned by researchers. We propose a detection method based on rich feature and convolution neural network. In order to avoid the interference of image content on classification, we use a high pass filter to preprocess the image, then a well-designed novel convolutional neural network is used to classify the images. In the experiment, the network performed better than traditional methods on the Columbia image splicing detection evaluation dataset.