Image recognition using fractal parameters

Concerns the applications of fractal theory to image recognition and we propose the method that can enhance learning rate and recognition rate by using fractal parameters that are composed of input vectors for a neural network in an image recognition model. Fractal parameters with the properties of self-similarity and recursiveness can recover lossless original images through iterating processes. Therefore the original image can be implicitly represented and uniquely mapped by fractal parameters. The enhanced result is shown by computer simulations.