CN109727362A - Banknote magnetic signal recognition methods based on discrete Fourier transform - Google Patents
Banknote magnetic signal recognition methods based on discrete Fourier transform Download PDFInfo
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- CN109727362A CN109727362A CN201811357492.4A CN201811357492A CN109727362A CN 109727362 A CN109727362 A CN 109727362A CN 201811357492 A CN201811357492 A CN 201811357492A CN 109727362 A CN109727362 A CN 109727362A
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Abstract
The present invention discloses a kind of banknote magnetic signal recognition methods based on discrete Fourier transform, comprising steps of to each channel standard magnetic signal data discrete Fourier transformation of predetermined quantity banknote, coefficient array is obtained, the invalid signals in the coefficient array is removed, obtains coefficient of efficiency array；The long value range of each mould of coefficient of efficiency array is obtained through data experiment, is denoted as threshold value array；By coefficient of efficiency array and the memory of threshold value array deposit banknote identification module；When banknote identifies, each single item of the coefficient of efficiency array stored in array to be detected and memory is subjected to the long difference comparsion of mould, according to comparison result, exports the judging result of banknote magnetic signal.The present invention may be implemented quickly to analyze the magnetic signal of the banknote of acquisition, to judge whether magnetic signal is problematic, to realize the quickly detection to banknote magnetic signal, realize banknote false distinguishing.
Description
Technical field
The present invention relates to signal processing technology fields, believe more particularly to a kind of banknote magnetic based on discrete Fourier transform
Number recognition methods.
Background technique
With advances in technology with development, the false distinguishing feature of banknote is more and more comprehensive, and magnetic is characterized in the weight of banknote false distinguishing
Want component part.Magnetic Sensor is all made of magnetic signal sensor in banknote identification module at present, and common algorithm is sentenced with logic
Based on disconnected.This method realizes complexity, and does not have versatility between different type banknote magnetic signal.
Summary of the invention
In view of the technical drawbacks of the prior art, it is an object of the present invention to provide one kind to become in discrete fourier
The banknote magnetic signal recognition methods changed, this method framework are clear, versatile.
The technical solution adopted to achieve the purpose of the present invention is:
A kind of banknote magnetic signal recognition methods based on discrete Fourier transform, comprising steps of
S1 obtains coefficient array to each channel standard magnetic signal data discrete Fourier transformation of predetermined quantity banknote,
After through threshold decision remove the invalid signals in the coefficient array, obtain coefficient of efficiency array；
S2 obtains the long value range of described each mould of coefficient of efficiency array through data experiment, is denoted as threshold value array；
The coefficient of efficiency array and threshold value array are stored in the memory of banknote identification module by S3；
When S4 banknote identifies, it is long that each single item of the coefficient of efficiency array stored in array to be detected and memory is subjected to mould
Difference comparsion exports the judging result of banknote magnetic signal according to comparison result.
In step S4, if the long difference of mould threshold value corresponding greatly, determine that the banknote magnetic signal is problematic.
In step S4, banknote magnetic signal data progress obtained is discrete when the array to be detected is by identifying banknote
Obtained from Fourier transformation.
It is further comprising the steps of before the step of described step S1:
The magnetic signal of the predetermined quantity banknote of acquisition is pre-processed, standard magnetic signal data are obtained.
It includes going to interfere, taking averaging operation that the magnetic signal, which carries out pretreatment,.
The present invention may be implemented quickly to analyze the magnetic signal of the banknote of acquisition, to judge whether magnetic signal asks
Topic realizes banknote false distinguishing to realize the quickly detection to banknote magnetic signal.
Detailed description of the invention
Fig. 1 show the flow diagram of the banknote magnetic signal recognition methods based on discrete Fourier transform；
Fig. 2 show magnetic signal figure；
Fig. 3 show Fourier transformation spectrogram.
Specific embodiment
The present invention is described in further detail below in conjunction with the drawings and specific embodiments.It should be appreciated that described herein
Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
As shown in Figure 1, the banknote magnetic signal recognition methods of the invention based on discrete Fourier transform includes:
S1 selects several banknotes to acquire magnetic signal data, and every banknote magnetic signal data include m data channel, each
Channel includes n data point.
S2 analysis handles several banknote magnetic signal data, including goes to interfere, takes averaging operation, obtains the standard magnetic of banknote
Signal data Data [m, n].
S3 carries out discrete Fourier transform to each channel magnetic signal, is decomposed into n triangular wave, i-th (i=0~m-1) is a
Channel data Datai[1, n] coefficient array obtained after converting is denoted as Fourier1i[1, n],
Wherein, coefficient array Fourier1i[1, n] is meant that Datai[1, n] corresponding curve is expressed as triangle letter
When several superpositions, the coefficient of i-th of wave function.Wherein, discrete Fourier transform formula are as follows:
Wherein x (n) is the data for the input that length is N,
WNIt is all n times unit roots,
X (k) is result of the x (n) after discrete Fourier transform.
S4 takes a threshold value ValidThres appropriate to each channel i (i=0~m-1)i(Thresi> 0), will
Fourier1iMould is long in [1, n] is less than ValidThresiItem be considered as invalid signals, be set to 0, obtained coefficient of efficiency array note
Make Fourier2i[1,n]。
The standard magnetic signal data Data [m, n] of S5 banknote, each channel data signal obtain after carrying out above-mentioned operation
Fourier transformation coefficient of efficiency array Fourier2 [m, n].
S6 carries out data experiment, obtains the long value range of coefficient of efficiency array Fourier2 [m, n] each mould, is denoted as threshold
It is worth array FourierThres2 [m, n].
Fourier2 [m, n], FourierThres2 [m, n] are stored in banknote identification module internal storage by S7.
When S8 carries out banknote identification, banknote magnetic signal data are denoted as NoteData [i, j], carry out discrete fourier change to it
It changes, the array obtained after transformation is denoted as NoteFourier [m, n].
S9 is poor by each single item progress mould length of the Fourier2 [m, n] stored in NoteFourier2 [m, n] and memory
Value compares, if difference threshold value FourierThres2 [m, n] corresponding greatly, determines that banknote magnetic signal is problematic.
The above is only a preferred embodiment of the present invention, it is noted that for the common skill of the art
For art personnel, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications
Also it should be regarded as protection scope of the present invention.
Claims (5)
1. the banknote magnetic signal recognition methods based on discrete Fourier transform, which is characterized in that comprising steps of
S1 obtains coefficient array, later to each channel standard magnetic signal data discrete Fourier transformation of predetermined quantity banknote
The invalid signals in the coefficient array are removed through threshold decision, obtain coefficient of efficiency array；
S2 obtains the long value range of described each mould of coefficient of efficiency array through data experiment, is denoted as threshold value array；
The coefficient of efficiency array and threshold value array are stored in the memory of banknote identification module by S3；
When S4 banknote identifies, each single item of the coefficient of efficiency array stored in array to be detected and memory is subjected to the long difference of mould
Compare, according to comparison result, exports the judging result of banknote magnetic signal.
2. the banknote magnetic signal recognition methods based on discrete Fourier transform as described in claim 1, which is characterized in that step S4
In, if the long difference of mould threshold value corresponding greatly, determine that the banknote magnetic signal is problematic.
3. the banknote magnetic signal recognition methods based on discrete Fourier transform as described in claim 1, which is characterized in that step S4
In, the array to be detected banknote magnetic signal data obtained when identifying banknote obtain and discrete Fourier transform
It arrives.
4. the banknote magnetic signal recognition methods based on discrete Fourier transform as described in claim 1, which is characterized in that described
It is further comprising the steps of before the step of step S1:
The magnetic signal of the predetermined quantity banknote of acquisition is pre-processed, standard magnetic signal data are obtained.
5. the banknote magnetic signal recognition methods based on discrete Fourier transform as claimed in claim 4, which is characterized in that described
It includes going to interfere, taking averaging operation that magnetic signal, which carries out pretreatment,.
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Cited By (2)
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| CN114419644A (en) * | 2021-12-30 | 2022-04-29 | 武汉卓目科技有限公司 | Banknote denomination recognition method and system |
| CN115392298A (en) * | 2022-08-12 | 2022-11-25 | 恒银金融科技股份有限公司 | Magnetic signal identification method |
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| CN109727362B (en) | 2022-03-08 |
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