A Hierarchical Target Recognition Method Based on Image Processing

A Hierarchical Target Recognition Method Based on Image Processing

QingE Wu (Zhengzhou University of Light Industry, China) and Weidong Yang (Fudan University, China)
DOI: 10.4018/978-1-5225-1884-6.ch005
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In order to provide an accurate and rapid target recognition method for some military affairs, public security, finance and other departments, this paper studies firstly a variety of fuzzy signal, analyzes the uncertainties classification and their influence, eliminates fuzziness processing, presents some methods and algorithms for fuzzy signal processing, and compares with other methods on image processing. Moreover, this paper uses the wavelet packet analysis to carry out feature extraction of target for the first time, extracts the coefficient feature and energy feature of wavelet transformation, gives the matching and recognition methods, compares with the existing target recognition methods by experiment, and presents the hierarchical recognition method. In target feature extraction process, the more detailed and rich texture feature of target can be obtained by wavelet packet to image decomposition to compare with the wavelet decomposition. In the process of matching and recognition, the hierarchical recognition method is presented to improve the recognition speed and accuracy. The wavelet packet transformation is used to carry out the image decomposition. Through experiment results, the proposed recognition method has the high precision, fast speed, and its correct recognition rate is improved by an average 6.13% than that of existing recognition methods. These researches development in this paper can provide an important theoretical reference and practical significance to improve the real-time and accuracy on fuzzy target recognition.
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Signal Processing Method To Fuzzy Image

Because of image acquisition system, different physical phenomena such as illumination cannot be completely evenly distributed, and many other reasons, the obtained edge intensity of image is different. Moreover, in real-world situations, image data is often contaminated by noise. While the scenery features mixed together so that it makes subsequent interpretation very difficult. To achieve the accurate grasp of the picture intent, it needs to study a target recognition method that can not only detect the non-continuity of intensity, but also can determine their exact position. It needs to develop new uncertainty processing methods and algorithms to solve such problems.

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