With the description of average Holder constant of fractional Brownian motion, and analyzing the different depth of 3D surface between the target and complex background, a novel method for artificial target recognition based on wavelet transformation and Holder constant was proposed. Examples of application of the algorithm to artificial target recognition were given. The anti interference capability was improved by using wavelet transformation. More accurate localization can be attained by using two images in the same region by different scale. This method is suitable for identifying specific targets in a complex background.