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Depth learning based and infrared geminate transistor employed authenticity identification method of currency detector

An infrared pairing tube and deep learning technology, applied in the field of infrared counterfeiting, can solve the problems of poor system stability and low accuracy rate, and achieve the effect of fast processing speed, high accuracy rate, and good counterfeit identification function

Active Publication Date: 2018-07-27
武汉卓目科技有限公司
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Problems solved by technology

However, this method is based on a simple comparison between the collected analog signals and the standard threshold of genuine banknotes to identify counterfeit, the system stability is poor, and the accuracy rate is low

Method used

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  • Depth learning based and infrared geminate transistor employed authenticity identification method of currency detector
  • Depth learning based and infrared geminate transistor employed authenticity identification method of currency detector
  • Depth learning based and infrared geminate transistor employed authenticity identification method of currency detector

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Embodiment

[0045] The deep learning-based infrared method for authenticating tubes of the present embodiment comprises the following steps:

[0046] See figure 1 , Step 1 is to verify the correctness of the signal according to the waveform of the infrared pair of tubes. In this embodiment, 100 yuan is detected and 6 pairs of infrared pair of tubes are installed in the banknote detector as an example. In this process, the correctness of the signal is verified by judging the denomination, version and currency of the banknote, the width of the banknote, and the presence or absence of the infrared tube waveform. The specific process is as follows:

[0047] Step 1.1 Determine whether the denomination of the banknote is 100 yuan, whether the version is 1999, 2005 or 2015, and whether the currency is RMB. If the denomination of the banknote is 100 yuan, the version is the 1999 version or the 2005 version or the 2015 version, and the currency is RMB, the three conditions are met at the same ti...

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Abstract

The invention discloses a depth learning based and infrared geminate transistor employed authenticity identification method of a currency detector and belongs to a field of infrared authenticity identification. The method includes performing signal correctness verification according to multiple channels of infrared geminate transistor waveforms; performing pretreatment on the multiple channels ofthe infrared geminate transistor waveforms; generating a two-dimensional array, converting to an image and processing; performing currency authenticity identification by utilizing the infrared geminate transistor waveforms and adopting CNN training and a detection process in depth learning. The method provided by the invention can realize a good authenticity identification function at a comparatively high processing speed with high accuracy.

Description

technical field [0001] The invention belongs to the technical field of infrared counterfeit identification, and in particular relates to an infrared counterfeit identification method for banknote detectors based on deep learning. . Background technique [0002] At present, the technique of making counterfeit banknotes with false ones makes people hard to guard against, especially the artificial anti-counterfeit marks in banknotes have been mostly imitated by counterfeiters. Therefore, only by identifying some conventional anti-counterfeiting features, such as: ultraviolet fluorescent reaction, magnetic ink and security thread to identify counterfeit, its accuracy rate is greatly reduced. Because the optically variable inks used in genuine banknote printing are highly confidential, it is difficult for counterfeiters to imitate the optically variable features of the ink areas of genuine banknotes. By comprehensively analyzing and judging the difference in infrared transmissi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G07D7/12G07D7/20G06N3/08
CPCG06N3/08G07D7/12G07D7/20
Inventor 周严周维曹宝莲
Owner 武汉卓目科技有限公司
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