A hierarchical target recognition method based on image processing

Anlai Sun, Wei Hu, Ying Xiong, Jian Li, QingE Wu


In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and otherdepartments, this paper studied firstly a variety of fuzzy signal, analyzed the uncertainties classification and their influence,eliminated fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compared with othermethods on image processing. Where, the fuzzy signal processing is that a blurred signal is dealt with by eliminating fuzziness.Moreover, this paper used the wavelet packet analysis to carry out feature extraction of target for the first time, extractedthe coefficient feature and energy feature of wavelet transformation, gave the matching and recognition methods, comparedwith the existing target recognition methods by experiment, and presented the hierarchical recognition method. In target featureextraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decompositionto compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition methodis presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the imagedecomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correctrecognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development inthis paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy onfuzzy target recognition.

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DOI: https://doi.org/10.5430/air.v3n3p1


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Artificial Intelligence Research

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