Application of Chaos in Image Processing and Recognition

The probability of generating chaos can be substantially increased by cross-iteration between a class of special quadratic functions and random ones, and the result in [1]-[3] shows that it is a better method to construct chaotic system. This paper works on the chaotic characteristic of the dynamic system that constitutes of a quadratic surface mapping and an image function in a spatial unit area, the chaotic attractor is discovered as a new characteristic for image recognition. The chaotic characteristic is analyzed by calculating the Lyapunov exponent and drawing the bifurcation diagram. It is found that the chaotic characteristic of discrete surface and image is similar to the continuum. The chaotic attractor changes with the parameters and surface control points, and so with the sequence images. In particular, the number of the attractor points but the distributive distinction can be changed by slightly adjusting the surface or image, and it has important significance for research on pattern recognition or vision mechanism. In addition, the experimental result shows that using the image chaotic attractor to recognize different human faces is measurable, of course, there are many problems should be researched necessarily.