Multi-currency-type and face value recognition method based on template feature points and topological structures of template feature points

A technology of topology structure and identification method, applied in character and pattern recognition, verification of the authenticity of banknotes, processing coins or valuable banknotes, etc. , the effect of high processing speed

Active Publication Date: 2015-03-25
BEIJING UNIV OF POSTS & TELECOMM
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In view of this, this application proposes a multi-currency face value recognition method based on Harri

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  • Multi-currency-type and face value recognition method based on template feature points and topological structures of template feature points
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  • Multi-currency-type and face value recognition method based on template feature points and topological structures of template feature points

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[0019] Below, the implementation of the technical solution will be further described in detail in conjunction with the accompanying drawings.

[0020] Those skilled in the art can understand that although the following description involves many technical details related to the embodiments of the present invention, this is only an example for illustrating the principle of the present invention, and does not imply any limitation. The present invention can be applied to occasions other than the technical details exemplified below, as long as they do not deviate from the principle and spirit of the present invention.

[0021] In addition, in order to avoid making the description in this manual limited to redundant, in the description in this manual, some technical details that can be obtained in the existing technical documents may be omitted, simplified, modified, etc. understandable to human beings, and this does not affect the adequacy of the disclosure of this specification. ...

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Abstract

The invention discloses a multi-currency-type and face value recognition method based on template feature points and topological structures of template feature points. The multi-currency-type and face value recognition method comprises the steps that 1 the feature points of paper currency images to be recognized are extracted and the positions and feature descriptions of the feature points are recorded; 2 first comparison matching is conducted on the feature points of the paper currency images to be recognized and reference points of templates respectively, the feature points of which matching results with the reference points of one or more templates meet first matching conditions are selected as the reference points of the paper currency images to be recognized; 3 the reference points of the paper currency images to be recognized are used as reference to generate topological structure information of other feature points; 4 second comparison matching is conducted on the feature descriptions of the other feature points of the paper currency images to be recognized and the topological structure information of other feature points and the feature descriptions and topological structure information of the feature points of one or more feature points; 5 currency types and face values represented by the templates are selected as face value recognition results of the paper currency images to be recognized, wherein the comparison matching results of the paper currency images to be recognized and the templates meet distinguishing conditions.

Description

technical field [0001] The invention belongs to the technical field of image pattern recognition, and relates to a multi-currency denomination method based on template feature points and its topological structure. Background technique [0002] The research on multi-currency face value recognition method has important practical value in intelligent banknote processing equipment, and relevant research results and products have been published at home and abroad. The banknote images collected by the image sensor have different feature patterns for images of different currencies and different denominations. The early banknote face value recognition methods were mostly based on neural networks [1]; in recent years, texture features have been used for banknote face value recognition. The method was proposed in [2]. Among the published face value recognition methods, texture features are the most discriminative, so extracting image texture features to represent banknotes of differe...

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Application Information

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IPC IPC(8): G07D7/20G07D7/202
Inventor 赵衍运李澜博庄伯金赵志诚苏菲
Owner BEIJING UNIV OF POSTS & TELECOMM
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