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DSmT (Dezert-Smarandache Theory)-based image target multi-characteristic fusion recognition method

A multi-feature fusion and recognition method technology, which is applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as incompleteness, low target recognition rate, high conflict, etc., to improve the correct recognition rate and effectively reject The effect of judgment ability

Inactive Publication Date: 2013-04-03
SOUTHEAST UNIV
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Problems solved by technology

[0005] Purpose of the invention: In order to overcome the deficiencies in the prior art, the present invention provides a multi-feature fusion recognition method that combines DSmT reasoning theory and PNN network to recognize image targets, and solves the problem of information acquisition in 3D target recognition. Inaccurate, uncertain, incomplete and highly conflicting problems lead to low target recognition rate

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  • DSmT (Dezert-Smarandache Theory)-based image target multi-characteristic fusion recognition method
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  • DSmT (Dezert-Smarandache Theory)-based image target multi-characteristic fusion recognition method

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[0026] The present invention will be further described below in conjunction with the accompanying drawings.

[0027] This project is supported by the National Natural Science Foundation of China (Youth Fund) (No.60804063); the Natural Science Foundation of Jiangsu Province (No.BK2010403); the Open Fund of the Key Laboratory of Image Information Processing and Intelligent Control of the Ministry of Education (No. 200902) ); Aviation Science Fund Project (20101690001); Innovation Fund of Southeast University (No.3208000501); Teaching and Research Funding Project for Outstanding Young Teachers of Southeast University (3208001203).

[0028] 1 Image Feature Extraction

[0029] The first step in image object recognition is to extract effective image features. Here, we mainly introduce moment feature quantity and profile feature quantity, moment feature quantity includes Hu moment, normalized moment of inertia (NMI) and affine invariant moment, and profile feature quantity includes ...

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Abstract

The invention discloses a DSmT (Dezert-Smarandache Theory)-based image target multi-characteristic fusion recognition method. The method comprises the steps: firstly, multiple characteristic quantities, such as moment, outline and the like of an image target, are extracted to serve as a data source to obtain enough useful complementary information; then, a target recognition rate matrix is constructed by a PNN (Probability Neural Network) widely used in classification; and then, a value is assigned to the basic reliability by the target recognition rate matrix according to an initial recognition result of the PNN and a rule similar to the maximum likelihood thought in the statistics; and finally, decision-level data infusion is carried out by using a DSmT combination rule to complete the recognition of the three-dimensional target. With the DSmt-based image target multiple features fusion method, the problem that the target recognition rate is not high, resulting from inaccuracy, indeterminacy and incompleteness of the obtained information and the high-degree conflict and the like is solved.

Description

technical field [0001] The present invention relates to the fields of image recognition and artificial intelligence, and in particular to a method for obtaining sufficient useful complementary information by extracting multiple features of an image target, and applying DSmT information fusion theory to fuse information at the decision-making level to obtain a final decision-making result . Background technique [0002] The recognition of 3D targets is one of the core problems in the field of computer vision. At present, the acquisition of 3D target information is mainly obtained through 2D digital images observed at any angle. There are many changes, which greatly increases the difficulty of using its two-dimensional digital image for target recognition. On the one hand, in the conversion process from 3D to 2D, the amount of information is lost. On the other hand, the establishment of the database is also incomplete. [0003] For the recognition of three-dimensional objec...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/66G06N3/08
Inventor 李新德杨伟东
Owner SOUTHEAST UNIV
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