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Banknote face orientation identification method and apparatus

A recognition method and banknote technology, applied in character and pattern recognition, biological neural network models, computer components, etc., can solve the problems of inconvenient recognition, affecting the speed and effect of recognition, cumbersome recognition process, etc., and achieve fast recognition speed Effect

Active Publication Date: 2015-08-26
SHENZHEN YIHUA COMP +2
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AI Technical Summary

Problems solved by technology

However, the neural network pattern recognition method requires a large number of sample tests, and it is difficult to achieve a 100% recognition rate.
This makes the recognition process relatively cumbersome, affects the speed and effect of recognition, and brings inconvenience to the recognition of banknotes

Method used

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  • Banknote face orientation identification method and apparatus
  • Banknote face orientation identification method and apparatus
  • Banknote face orientation identification method and apparatus

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Embodiment Construction

[0024] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, but not to limit the present invention. In addition, it should be noted that, for the convenience of description, only parts related to the present invention are shown in the drawings but not all content.

[0025] image 3 It is a schematic flowchart of a banknote-oriented identification method provided by the first embodiment of the present invention. The method of this embodiment can be executed by a banknote-oriented identification device, which can be implemented by means of hardware and / or software, and generally It can be integrated in an ATM terminal with scrollable output and storage.

[0026] see image 3 , the banknote-oriented identification method, comprising:

[0027] Step S101, selecting the first identification ...

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Abstract

The embodiment of the invention discloses a banknote face orientation identification method and apparatus. The banknote face orientation identification method comprises steps of selecting a first identification area, a second identification area, a third identification area and a fourth identification area of an obtained banknote image according to preset positions; calculating the sum of pixel gray values of the first identification area, the sum of pixel gray values of the second identification area, the sum of pixel gray values of the third identification area and the sum of pixel gray values of the fourth identification area; comparing the sum of the pixel gray values of the first identification area and the sum of the pixel gray values of the second identification area; comparing the sum of the pixel gray values of the third identification area and the sum of the pixel gray values of the fourth identification area; and determining the face orientation of the banknote image according to comparing results. By employing the identification method and apparatus, the input face orientation of an input banknote can be accurately and rapidly identified.

Description

technical field [0001] The invention relates to the field of banknote identification, in particular to a banknote-oriented identification method and device. Background technique [0002] Banknote face-to-face recognition is the basic recognition part of banknote verification, and the result of face-to-face recognition will be used for subsequent processing. Only after the face of the banknote is determined can the banknote be accurately identified. However, due to the fact that there are various specifications of banknotes, and they are prone to be bent and stained during use, the banknotes to be identified show different characteristics. [0003] In order to overcome the above-mentioned problems, at present, a recognition algorithm based on a neural network is used to recognize the face of the banknote. That is to obtain batch sample data of banknotes, then extract features, train the neural network, test the convergence of the neural network and the recognition rate of t...

Claims

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Application Information

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IPC IPC(8): G07D7/20G06N3/02
Inventor 黄勃
Owner SHENZHEN YIHUA COMP
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