Applied Mathematics & Information Sciences

Author Country (or Countries)



This paper presents a novel fragile watermarking scheme based on an artificial neural network (ANN). The fragile watermark is designed according to the characteristics of the original image. If the image is modified, the alteration can be detected via the fragile watermark without original image. Based on the type of alteration, we can determine what modifications have been performed. An artificial neural network is used to analyze the modifications. The experimental results show that the proposed method can detect tampering, locate where the tampering has occurred, and recognize what kind of alteration has occurred. This method has a high success ratio in recognizing the types of modifications and provides sufficient evidence. The experimental results demonstrate that our method is indeed effective.