A hierarchical target recognition method based on image processing
Author(s) -
Anlai Sun,
Wei Hu,
Ying Xiong,
Jian Li,
QingE Wu
Publication year - 2014
Publication title -
artificial intelligence research
Language(s) - English
Resource type - Journals
eISSN - 1927-6982
pISSN - 1927-6974
DOI - 10.5430/air.v3n3p1
Subject(s) - wavelet packet decomposition , computer science , artificial intelligence , pattern recognition (psychology) , wavelet , feature extraction , feature (linguistics) , fuzzy logic , transformation (genetics) , wavelet transform , image processing , process (computing) , stationary wavelet transform , signal processing , matching (statistics) , computer vision , image (mathematics) , mathematics , digital signal processing , philosophy , statistics , operating system , linguistics , computer hardware , biochemistry , chemistry , gene
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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