Chaotic attractor of the image
It is necessary and meaningful to study the chaotic characteristics of the image function. The applications of chaotic research in image recognition are discussed in literature [1-3]. Up until now, there are no such applicative examples that are taking an image as function to construct dynamic system. In curve iteration, when one curve is adjusted to a standard one in unit area, the other is a random generated one, the probability of chaos is above 10% . We call the standard curve in the unit area as auxiliary surface (auxiliary function). In literature, it turns out that when sine functions or wavelet functions are taken as auxiliary surface, the other surface is generated randomly, chaos can be brought more easily. Based on these works, this paper researches chaotic characteristics of the image. Section 2 shows that dynamic system of Gaussian function and image can bring on chaos. In section 3, construct three dynamic systems by Gaussian function and three dierent groups of human face images, it is found that the shape of attractors are close to each other when human faces are similar.