Image Target Recognition by Eliminating Fuzziness on Image and Wavelet Transformation

How to carry out the fuzzy signal processing to an image is a problem to be solved urgently in many departments. For fuzziness on image processing, this paper studies a variety of fuzzy signal, implements the denoising fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compares with other methods on image processing. At the same time, this paper uses the wavelet analysis to carry out feature extraction of target for the first time, extracts the coefficient feature and energy feature of image decomposition, gives the matching and recognition methods, compares with the existing target recognition methods by experiment, and presents a target recognition method based on region of interest. Using the combining method of simulation and instance experiments, this paper systematically analyzes the validity of the model and algorithms. Moreover, using the wavelet transform to carry out the image decomposition, this paper extracts the coefficient feature of wavelet transform, gives the matching and recognition methods, and compares with the existing target recognition methods by experiment. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 5.16% than that of existing recognition methods. These researches in this paper can provide a new way of thinking for the researchers in pattern recognition field.