WO2015085815A1 - 一种厚度异常钞票的识别方法及系统 - Google Patents

一种厚度异常钞票的识别方法及系统 Download PDF

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Publication number
WO2015085815A1
WO2015085815A1 PCT/CN2014/087746 CN2014087746W WO2015085815A1 WO 2015085815 A1 WO2015085815 A1 WO 2015085815A1 CN 2014087746 W CN2014087746 W CN 2014087746W WO 2015085815 A1 WO2015085815 A1 WO 2015085815A1
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Prior art keywords
thickness
signal
abnormal
banknote
thickness signal
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PCT/CN2014/087746
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English (en)
French (fr)
Inventor
梁添才
王晓亮
陈�光
刘思伟
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广州广电运通信息科技有限公司
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Application filed by 广州广电运通信息科技有限公司 filed Critical 广州广电运通信息科技有限公司
Priority to AU2014361443A priority Critical patent/AU2014361443B2/en
Priority to US15/102,443 priority patent/US20160358399A1/en
Priority to EP14868904.5A priority patent/EP3082113A4/en
Publication of WO2015085815A1 publication Critical patent/WO2015085815A1/zh
Priority to ZA2016/03994A priority patent/ZA201603994B/en

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    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07D—HANDLING OF COINS OR VALUABLE PAPERS, e.g. TESTING, SORTING BY DENOMINATIONS, COUNTING, DISPENSING, CHANGING OR DEPOSITING
    • G07D7/00—Testing specially adapted to determine the identity or genuineness of valuable papers or for segregating those which are unacceptable, e.g. banknotes that are alien to a currency
    • G07D7/16—Testing the dimensions
    • G07D7/164—Thickness
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65H—HANDLING THIN OR FILAMENTARY MATERIAL, e.g. SHEETS, WEBS, CABLES
    • B65H43/00—Use of control, checking, or safety devices, e.g. automatic devices comprising an element for sensing a variable
    • B65H43/04—Use of control, checking, or safety devices, e.g. automatic devices comprising an element for sensing a variable detecting, or responding to, presence of faulty articles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
    • B65H—HANDLING THIN OR FILAMENTARY MATERIAL, e.g. SHEETS, WEBS, CABLES
    • B65H2701/00—Handled material; Storage means
    • B65H2701/10—Handled articles or webs
    • B65H2701/19—Specific article or web
    • B65H2701/1912—Banknotes, bills and cheques or the like

Definitions

  • Embodiments of the present invention relate to the field of banknote processing technologies, and in particular, to a method and system for identifying banknotes of abnormal thickness.
  • the abnormal thickness banknotes discussed below are mainly classified into currency notes, which are classified into two types: damaged banknotes and altered banknotes.
  • damaged banknotes refer to the banknotes formed by the application of the pasting method to restore the old banknotes.
  • the circulation of the damaged banknotes in the market seriously affects the banknote image and the country.
  • Image according to the relevant regulations of the central bank, such banknotes should be recycled and destroyed in a centralized manner; changing coins means that criminals recombine banknotes from different sheets by means of pasting, digging, etc., and the formed banknotes are pasted and dug. Other ways can often add value. Since the damaged currency and the altered coin have certain harmful effects on the national, collective and personal interests, the financial counterfeiting equipment needs to have the ability to clear abnormal banknotes of thickness.
  • the existing financial money detector type device recognizes an abnormal thickness banknote by setting a thickness sensor and applying a sliding search method to identify the collected banknote thickness signal.
  • the number of thickness sensors of the existing financial banknote type equipment is relatively small, and the banknote passage is ensured to ensure smooth banknotes.
  • the width is relatively wide, which causes a certain gap between the thickness sensors.
  • the banknote thickness signal is identified, and when the sliding window is located at the peak position of the harmonic signal, since the amplitude of the thickness signal of the region is high, there is a case where the region is mistaken for the thickness abnormality, thereby determining the normal banknote. Abnormal banknotes for thickness.
  • the embodiment of the invention provides a method and a system for identifying abnormal thickness banknotes.
  • the normal banknote caused by the fluctuation of the amplitude of the harmonic signal can be effectively solved with a smaller calculation amount. Misjudgment and problems such as defective banknotes due to under-sampling of signals, and missing coins.
  • Multi-channel collecting the thickness signal of the banknote to obtain a multi-channel thickness signal
  • the fusion result is identified to obtain a recognition result.
  • the method further includes:
  • the preprocessed multipath thickness signals are stored.
  • the method further includes:
  • the banknotes are sorted and sent to a position corresponding to the category based on the recognition result.
  • the step of preprocessing the multipath thickness signal includes:
  • An effective signal region determination is performed on the denoising processing signal to obtain an effective region.
  • Steps: searching for a mutation point in the multipath thickness signal according to a preset rule, and forming a mutation point set includes:
  • the mutation point is stored in a set of mutation points.
  • the system for identifying an abnormal thickness banknote includes: a thickness sensor, a DSP chip, an embedded module and a mechanical motion module;
  • the thickness sensor is connected to the DSP chip for collecting a thickness signal of the banknote
  • the DSP chip is connected to the embedded module, and configured to analyze and identify the banknote according to the thickness signal to obtain a recognition result;
  • the embedded module is connected to the mechanical motion module, and configured to control the mechanical motion module according to the recognition result;
  • the mechanical motion module is configured to classify the banknotes according to a control instruction set of the embedded module and send the banknotes to a position corresponding to the category.
  • the system also includes a storage module for storing the identification result.
  • the thickness sensor is a multi-way thickness sensor.
  • the method for identifying an abnormal thickness banknote firstly collects a thickness signal of the banknote to obtain a multi-path thickness signal; and then preprocesses the multi-path thickness signal; and then searches the multi-path thickness signal according to a preset rule.
  • the method and system for identifying abnormal thickness banknotes can effectively solve the misjudgment and the cause of normal banknotes caused by the fluctuation of the amplitude of the harmonic signals by detecting the sudden change of the thickness signal. Problems such as the loss of banknotes due to under-sampling of signals, and the detection of missing coins.
  • FIG. 1 is a schematic diagram of the banknotes of the damaged banknotes
  • Figure 2 is a schematic diagram of the thickness signal of the damaged banknote
  • FIG. 3 is a schematic diagram of a prior art application of a sliding search method for identifying a banknote thickness signal
  • FIG. 4 is a schematic diagram of a harmonic signal encountered when a banknote thickness signal is recognized by a sliding search method in the prior art
  • FIG. 5 is a flow chart of a first embodiment of a method for identifying an abnormal thickness banknote according to an embodiment of the present invention
  • FIG. 6 is a schematic diagram of a type of abrupt point in an embodiment of the present invention.
  • FIG. 7 is a schematic diagram of an abnormal region of a thickness signal abnormality according to an embodiment of the present invention.
  • FIG. 8 is a flow chart of a second embodiment of a method for identifying an abnormal thickness banknote according to an embodiment of the present invention.
  • Figure 9 is a schematic view showing the change of banknotes in the second embodiment of the present invention.
  • FIG. 10 is a schematic diagram of a coin thickness signal according to a second embodiment of the present invention.
  • Figure 11 is a schematic view showing a collection of abrupt points in a second embodiment of the present invention.
  • FIG. 12 is a schematic view showing an abnormal thickness region of a second embodiment of the present invention.
  • FIG. 13 is a schematic structural diagram of an embodiment of an identification system for an abnormal thickness banknote according to an embodiment of the present invention.
  • the embodiment of the invention provides a method and a system for identifying abnormal thickness banknotes.
  • the normal banknote caused by the fluctuation of the amplitude of the harmonic signal can be effectively solved with a smaller calculation amount. Misjudgment and problems such as defective banknotes due to under-sampling of signals, and missing coins.
  • the method and system for identifying abnormal thickness banknotes in the embodiments of the present invention can be used not only for the identification of banknotes, but also for identifying sheet-like documents such as checks, which are not limited herein.
  • the method and apparatus of the embodiment of the present invention will be described below by taking the identification of the banknote as an example. Although the identification of the banknote is only taken as an example, it should not be construed as limiting the method and apparatus of the present invention.
  • a first embodiment of a method for identifying an abnormal thickness banknote according to an embodiment of the present invention includes:
  • the multi-channel thickness sensor can first be used to collect the thickness signal of the banknote, and a multi-channel thickness signal can be obtained.
  • the multi-path thickness signal can be pre-processed to identify the multi-path thickness signal.
  • the mutation points in the multi-path thickness signal can be searched according to a preset rule to form a set of the mutation points.
  • the above mutation point may include an upper mutation point and a lower mutation point, and the set of the above mutation points is called a mutation point collection.
  • the abnormal thickness region of the thickness of the multi-path thickness signal can be determined according to the set of the mutation points.
  • the thickness abnormality area mentioned above may include a suspicious area starting to be deformed, a suspicious area of an up-down type, and a suspicious area of an up-and-down type.
  • the starting point of the area 1 is the signal starting point, and the ending point is the lower modification type mutation point, and the area 1 is called the start sub-variable suspicious area.
  • the area 2 is the upper variable and the suspicious area
  • the area 3 is the upper variable. End suspicious area.
  • the thickness abnormal region of the multi-path thickness signal may be determined according to the thickness abnormality suspect region, and the position and area of the thickness signal abnormal region may be marked.
  • the position and area of the thickness signal abnormal region of the multi-path thickness signal can be fused to obtain a fusion result.
  • the fusion result After the fusion result is obtained, the fusion result can be identified and the recognition result can be obtained.
  • the method for identifying an abnormal thickness banknote firstly collects a thickness signal of a banknote to obtain a multi-path thickness signal; and then preprocesses the multi-path thickness signal; and then searches for a mutation point in the multi-path thickness signal according to a preset rule. And constituting a set of mutated points; then determining a thickness anomaly area of the multi-path thickness signal according to the set of mutated points; then determining an abnormal thickness area of the multi-path thickness signal according to the suspicious area of the thickness abnormality, and marking the position and area of the abnormal area of the thickness signal; The position and area of the abnormal region of the thickness signal of the multi-path thickness signal are fused to obtain the fusion result.
  • the method of the embodiment of the invention can effectively solve the normality caused by the fluctuation of the amplitude of the harmonic signal by detecting the sudden change point of the thickness signal, with a smaller calculation amount. Mistakes in banknotes and the loss of banknotes due to under-sampling of signals, and the detection of missing coins.
  • a second embodiment of the identification method includes:
  • multi-channel collecting the thickness signal of the banknote to obtain a multi-channel thickness signal
  • the multi-channel thickness sensor can first be used to collect the thickness signal of the banknote, and a multi-channel thickness signal can be obtained.
  • the multi-path thickness signal can be pre-processed to identify the multi-path thickness signal.
  • the pre-processing operation may include: sampling the multi-path thickness signal to obtain a sampling processing signal; performing denoising processing on the sampling processing signal to obtain a denoising processing signal; and performing effective signal region determination on the denoising processing signal to obtain Effective area.
  • the above pretreatment operation is mainly used to reduce the influence of the outside on the thickness signal.
  • the multi-path thickness signal in the effective area can be stored.
  • the pre-processed multi-path thickness signal can be stored in the internal memory of the processor.
  • the mutation points in the multipath thickness signal can be searched according to a preset rule to form a set of the mutation points.
  • the above mutation point may include an upper mutation point and a lower mutation point, and the set of the above mutation points is called a mutation point collection.
  • the searching for a mutation point in the multipath thickness signal according to a preset rule, and the specific process of forming the mutation point set may include:
  • the judgment condition of the upper variant mutation point and the lower variant mutation point is read; the mutation point is searched from the multipath thickness signal according to the judgment condition; and the mutation point is stored in the mutation point set.
  • the abnormal thickness region of the thickness of the multi-path thickness signal can be determined according to the set of the mutation points.
  • the thickness abnormality area mentioned above may include a suspicious area starting to be deformed, a suspicious area of an up-down type, and a suspicious area of an up-and-down type.
  • the starting point of area 1 in Figure 7 is the letter The starting point of the number is the lowering type of the mutation point, and the area 1 is called the suspicious area of the next variant.
  • the area 2 is the suspicious area of the upper subversion and the area 3 is the suspicious area of the upper end type.
  • the thickness abnormal region of the multi-path thickness signal may be determined according to the thickness abnormality suspect region, and the position and area of the thickness signal abnormal region may be marked.
  • the position and area of the thickness signal abnormal region of the multi-path thickness signal can be fused to obtain a fusion result.
  • the fusion result can be identified and the recognition result can be obtained. If the fusion result is an abnormal area covering the authentication area, the banknote is identified as a coin-changing coin; if the fusion result is that the area of the abnormal area exceeds a fixed threshold, the banknote is identified as a damaged banknote; otherwise, the banknote is identified as a banknote .
  • the above fixed threshold value is set in advance according to the banknote to be tested and the device structure, and is not limited herein.
  • the banknotes are sorted and sent to the position corresponding to the category according to the recognition result, for example, different types of banknotes can be transferred to the predetermined position, thereby completing the banknote recognition.
  • the banknote thickness to be detected is set to THK ⁇ 0.15THK, and the minimum paste thickness that the sensor can detect is thk.
  • the first step multi-channel collecting the thickness signal of the banknote
  • the Hall sensor is used to collect the banknote thickness signal, and the total M road thickness signal is used.
  • the number of sampling points of each signal is N.
  • FIG. 9 is a schematic diagram of the banknotes of the coin, and the sensor 1 and the sensor during the banknote process. 2 Covering the foreign matter pasting area, the sensor M does not cover the banknote area. See Figure 10 for the specific acquisition pattern of the thickness signals collected by each sensor.
  • the second step pre-processing the multi-path thickness signal
  • This process completes the sampling, denoising and effective area extraction of the thickness signal, and records the pre-processed signal as S(i,j), which can be stored in the internal storage unit of the signal processing chip for use in subsequent steps.
  • the effective area of the thickness signal extracted by the preprocessing process is as shown in the black frame selection area in FIG.
  • the third step searching for the mutation points in the multi-path thickness signal according to the preset rule to form a set of the mutation points;
  • Q i (j) 0, indicating that the jth sampling point of the i channels of the signal is not a sub-variation mutation point.
  • the fourth step determining an abnormally suspicious area of the thickness of the multi-path thickness signal according to the set of the mutation points;
  • PQ i is a set of mutation point markers for characterizing the i-th signal
  • the starting point of the suspect area is P start (i), and the length is abs (PQ i (j)) - P start (i);
  • the starting point of the suspect region is abs (PQ i (j)), and the length is m;
  • the above method is used to detect that there is two suspicious regions of the upper-thickness variable in the thickness signal of the first pass, and that there is a suspicious region in the second-thickness thickness signal.
  • Step 5 determining an abnormal thickness region of the multi-path thickness signal according to the suspicious area of the abnormal thickness, and marking the position and area of the abnormal region of the thickness signal;
  • abnormal region thickness mean threshold T Thk THK + ⁇ * thk
  • abnormal region thickness standard deviation threshold T std abnormal region length threshold T l is 1 cm width corresponding to the number of signal sampling points (this value can be based on the signal sampling frequency And banknote speed calculation);
  • the starting point of the i-th thickness abnormal suspicious area is s, and the length is l.
  • Calculating the thickness of the suspicious area, the average value Thk s and the standard deviation Std s can be calculated by the following formula.
  • the area is a thickness abnormal area, that is, the area is determined to be an abnormal thickness area when the area satisfies the following conditions.
  • T std and T l are empirical parameters.
  • the position of the thickness anomaly area is Area(k), and its area is S Area(k) (k means that the area is the kth thickness abnormal area of the banknote, assuming a total of N thickness abnormal areas), if the thickness is abnormal, the suspicious area If the mean and standard deviation characteristics do not satisfy the above determination conditions, the suspiciousness of the suspect area is excluded.
  • the method for detecting the first road thickness signal has two signal abnormal regions Area(1) and Area(2), and the second road thickness signal has a signal abnormal region.
  • Area (3) whose areas are S Area(1) , S Area(2), and S Area(3) .
  • Step 6 merging the position and area of the abnormal region of the thickness signal of the multi-path thickness signal to obtain the fusion result and identifying;
  • the relevant constraints include: the location of the authentication area Area N (this parameter is set according to different currencies and different denominations, for example, the RMB 100 authentication area is set as the watermark area and the national emblem area), and the thickness anomaly area threshold T S (this The values can be set according to different test standards, such as the ECB European Central Bank standard of 4 cm 2 ).
  • the thickness abnormal region position Area(k) and the thickness abnormal region area S Area(k) obtained by the above algorithm the thickness abnormal region position Area of the entire banknote and the total area of the abnormal region S Area are calculated.
  • the final recognition result is given.
  • the thickness abnormal area covers the banknote authentication area Area N , it is judged that the banknote is a coin, and when the thickness abnormal area does not cover the forgery area and the thickness abnormal area
  • the area is larger than the abnormal area area threshold T S , it is judged that the banknote is a damaged bank, otherwise the banknote is judged to be a banknote.
  • the thickness anomaly area Covers the watermark area and the area of the abnormal area It is greater than the abnormal area area threshold T S , and the banknote is judged to be a coin.
  • the method of the embodiment of the invention can effectively solve the misjudgment of the normal banknote caused by the fluctuation of the amplitude of the harmonic signal and the damage caused by the undersampling of the signal by detecting the sudden change of the thickness signal.
  • an identification system for the thickness abnormal banknote includes : thickness sensor 131, DSP chip 132, embedded module 133 and mechanical motion module 134;
  • a thickness sensor 131 connected to the DSP chip 132 for collecting a thickness signal of the banknote
  • the DSP chip 132 is connected to the embedded module 133 for analyzing and identifying the banknote according to the thickness signal to obtain a recognition result;
  • the embedded module 133 is connected to the mechanical motion module 134 for controlling the mechanical motion module 134 according to the recognition result;
  • the mechanical motion module 134 is configured to classify the banknotes according to the control instruction set of the embedded module 133 and send them to a position corresponding to the category.
  • the thickness sensor 131 first collects the thickness signal of the banknote, and transmits the thickness signal to the DSP chip 132 for analysis and identification. After the DSP chip 132 obtains the recognition result, the recognition result is transmitted to the embedded system 133, and is embedded.
  • the system 133 controls the mechanical motion module 134 to transfer the banknotes, the damaged banknotes, and the altered coins to different banknotes to enable classification of different types of banknotes.
  • the system also includes a storage module 135 for storing the recognition result.
  • the thickness sensor 131 is a multi-way thickness sensor.
  • the system of the embodiment of the invention can effectively solve the misjudgment of the normal banknote caused by the fluctuation of the amplitude of the harmonic signal and the damage caused by the undersampling of the signal by detecting the sudden change of the thickness signal.

Abstract

一种厚度异常钞票的识别方法及系统。该方法包括：多路采集钞票的厚度信号，得到多路厚度信号（501）；对多路厚度信号预处理（502）；根据预设规则搜索多路厚度信号内的突变点，构成突变点集合（503）；根据突变点集合确定多路厚度信号的厚度异常可疑区域（504）；根据厚度异常可疑区域确定多路厚度信号的厚度信号异常区域，并标记厚度信号异常区域的位置与面积（505）；将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果（506）；对融合结果进行识别，得到识别结果（507）。该识别方法通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。

Description

一种厚度异常钞票的识别方法及系统 技术领域
本发明实施例涉及纸币处理技术领域，尤其涉及一种厚度异常钞票的识别方法及系统。
背景技术
以下讨论的厚度异常钞票主要区分于流通钞，分为残损钞和变造币两种。在钞票流通过程中，经常发生撕裂、掉角等残旧情况，残损钞是指应用粘贴的方式将残旧钞票复原而形成的钞票，残损钞在市面上的流通严重影响了钞票形象和国家形象，根据央行相关规定这种钞票应该被回收，并进行集中销毁；变造币是指不法分子将来自不同张的钞票残券通过粘贴、挖补等方式重新组合，形成的钞票，通过粘贴、挖补等方式往往能够实现增值。由于残损币和变造币对国家、集体和个人利益均存在一定的危害性，因此金融验钞类设备需要具备清分厚度异常钞票的能力。
现有的金融验钞类设备通过设置厚度传感器，并应用滑动搜索方法识别采集到的钞票厚度信号的方式来识别厚度异常钞票。
但是由于机器成本和整机结构等原因的限制，请参阅图1及图2，现有金融验钞类设备厚度传感器的个数相对较少，加之为确保钞票的走钞顺畅，走钞通道的宽度相对较宽，这就造成了厚度传感器之间存在一定间隙，当粘贴在钞票表面的异物在走钞过程中恰好从两个传感器之间的间隙通过时，就会发生钞票异物区域厚度信号跳起相比正常值略低的情况，这种情况下应用滑动窗口搜索厚度异常区域可能会发生失效，造成异物粘贴钞票的漏检。
请参阅图3及图4，在钞票厚度信号采集过程中，存在走钞过程中钞票不平，以及电磁干扰等情况，这些情况可能造成正常钞票的厚度信号中包含谐波信号(即出现类似波浪形状的信号)。在应用滑动搜索的方法识别钞票厚度信号，并当滑动窗位于谐波信号的波峰位置时，由于该区域厚度信号幅值较高，存在将该区域误认为厚度异常的情况，从而将正常钞票判定为厚度异常钞。
发明内容
本发明实施例提供了一种厚度异常钞票的识别方法及系统，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
本发明实施例提供的厚度异常钞票的识别方法，包括：
多路采集钞票的厚度信号，得到多路厚度信号；
对所述多路厚度信号预处理；
根据预设规则搜索所述多路厚度信号内的突变点，构成突变点集合；
根据所述突变点集合确定所述多路厚度信号的厚度异常可疑区域；
根据所述厚度异常可疑区域确定所述多路厚度信号的厚度信号异常区域，并标记所述厚度信号异常区域的位置与面积；
将所述多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；
对所述融合结果进行识别，得到识别结果。
可选地，
在步骤对所述多路厚度信号预处理之后及步骤根据预设规则搜索所述多路厚度信号内的突变点之前还包括：
将经过预处理的多路厚度信号进行存储。
可选地，
在步骤对所述融合结果进行识别，得到识别结果之后还包括：
根据所述识别结果将所述钞票分类并送至与类别相对应的位置。
可选地，
步骤对所述多路厚度信号预处理包括：
对所述多路厚度信号进行抽样处理，得到抽样处理信号；
对所述抽样处理信号进行去噪处理，得到去噪处理信号；
对所述去噪处理信号进行有效信号区域确定，得到有效区域。
可选地，
步骤所述根据预设规则搜索所述多路厚度信号内的突变点，构成突变点集合包括：
读取上变型突变点和下变型突变点的判断条件；
根据所述判断条件从所述多路厚度信号内搜索突变点；
将所述突变点存执突变点集合。
本发明实施例提供的厚度异常钞票的识别系统，包括：厚度传感器、DSP芯片、嵌入式模块和机械运动模块；
所述厚度传感器，与所述DSP芯片相连，用于采集钞票的厚度信号；
所述DSP芯片，与所述嵌入式模块相连，用于根据所述厚度信号对所述钞票进行分析识别，得到识别结果；
所述嵌入式模块，与所述机械运动模块相连，用于根据所述识别结果控制所述机械运动模块；
所述机械运动模块，用于根据所述嵌入式模块的控制指令集将所述钞票进行分类并送至与类别相对应的位置。
可选地，
所述系统还包括存储模块，用于存储所述识别结果。
可选地，
所述厚度传感器为多路厚度传感器。
本发明实施例的厚度异常钞票的识别方法，首先多路采集钞票的厚度信号，得到多路厚度信号；然后对所述多路厚度信号预处理；接着根据预设规则搜索所述多路厚度信号内的突变点，构成突变点集合；然后根据所述突变点集合确定所述多路厚度信号的厚度异常可疑区域；接着根据所述厚度异常可疑区域确定所述多路厚度信号的厚度信号异常区域，并标记所述厚度信号异常区域的位置与面积；然后将所述多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；最后对所述融合结果进行识别，得到识别结果。本发明实施例厚度异常钞票的识别方法及系统，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
附图说明
图1为残损钞走钞示意图；
图2为残损钞的厚度信号示意图；
图3为现有技术应用滑动搜索方法识别钞票厚度信号的示意图；
图4为现有技术应用滑动搜索方法识别钞票厚度信号时遇到谐波信号的示意图；
图5为本发明实施例中厚度异常钞票的识别方法第一实施例流程图；
图6为本发明实施例中突变点类型示意图；
图7为本发明实施例中厚度信号异常可疑区域示意图；
图8为本发明实施例中厚度异常钞票的识别方法第二实施例流程图；
图9为本发明第二实施例中变造币走钞示意图；
图10为本发明第二实施例中变造币厚度信号示意图；
图11为本发明第二实施例中突变点集合示意图；
图12为本发明第二实施例中厚度异常可疑区域示意图；
图13为本发明实施例中厚度异常钞票的识别系统实施例结构示意图。
具体实施方式
本发明实施例提供了一种厚度异常钞票的识别方法及系统，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
需要说明的是，本发明实施例厚度异常钞票的识别方法及系统不仅可以用于钞票的识别，还可以用于识别支票等薄片类文件，在此处不作限定。下面以钞票的识别为例对本发明实施例的方法及装置进行说明，虽然仅以钞票的识别为例进行说明，但是不应将此作为本发明方法及装置的限定。
请参阅图5，本发明实施例中厚度异常钞票的识别方法的第一实施例包括：
501、多路采集钞票的厚度信号，得到多路厚度信号；
在对钞票进行识别之前，首先可以利用多路厚度传感器采集钞票的厚度信号，可以得到多路厚度信号。
502、对多路厚度信号预处理；
得到多路厚度信号之后，可以对多路厚度信号进行预处理操作，以便对多路厚度信号进行识别。
503、根据预设规则搜索多路厚度信号内的突变点，构成突变点集合；
对多路厚度信号进行预处理之后，可以根据预设规则搜索多路厚度信号内的突变点，构成突变点集合。
请参阅图6，上述的突变点可以包括上突变点和下突变点，上述的突变点构成的集合称为突变点集合。
504、根据突变点集合确定多路厚度信号的厚度异常可疑区域；
得到突变点集合之后，可以根据突变点集合确定多路厚度信号的厚度异常可疑区域。请参阅图7，上述的厚度异常可疑区域可以包含开始下变型可疑区域、上变下变型可疑区域和上变结束型可疑区域。图7中区域1的起始点为信号开始点，结束点为下变型突变点，称区域1为开始下变型可疑区域，类似的，称区域2为上变下变型可疑区域，区域3为上变结束型可疑区域。
505、根据厚度异常可疑区域确定多路厚度信号的厚度异常区域，并标记所述厚度信号异常区域的位置与面积；
确定多路厚度信号的厚度异常可疑区域之后，可以根据厚度异常可疑区域确定多路厚度信号的厚度异常区域，并标记厚度信号异常区域的位置与面积。
506、将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；
标记厚度信号异常区域的位置与面积之后，可以将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果。
507、对融合结果进行识别，得到识别结果。
得到融合结果之后，可以对融合结果进行识别，得到识别结果。
本发明实施例的厚度异常钞票的识别方法，首先多路采集钞票的厚度信号，得到多路厚度信号；然后对多路厚度信号预处理；接着根据预设规则搜索多路厚度信号内的突变点，构成突变点集合；然后根据突变点集合确定多路厚度信号的厚度异常可疑区域；接着根据厚度异常可疑区域确定多路厚度信号的厚度异常区域，并标记厚度信号异常区域的位置与面积；然后将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；最后对融合结果进行识别，得到识别结果。本发明实施例的方法，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常 钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
上面简单介绍了本发明厚度异常钞票的识别方法的第一实施例，下面对本发明厚度异常钞票的识别方法的第二实施例进行详细的描述，请参阅图8，本发明实施例中厚度异常钞票的识别方法的第二实施例包括：
801、多路采集钞票的厚度信号，得到多路厚度信号；
在对钞票进行识别之前，首先可以利用多路厚度传感器采集钞票的厚度信号，可以得到多路厚度信号。
802、对多路厚度信号预处理；
得到多路厚度信号之后，可以对多路厚度信号进行预处理操作，以便对多路厚度信号进行识别。上述的预处理操作具体可以包括：对多路厚度信号进行抽样处理，得到抽样处理信号；对抽样处理信号进行去噪处理，得到去噪处理信号；对去噪处理信号进行有效信号区域确定，得到有效区域。上述的预处理操作主要用于降低外界对厚度信号的影响。
803、将经过预处理的多路厚度信号进行存储；
对多路厚度信号预处理之后，可以将有效区域内的多路厚度信号进行存储，具体的，可以将经过预处理的多路厚度信号存储在处理器的内部存储器。
804、根据预设规则搜索多路厚度信号内的突变点，构成突变点集合；
将经过预处理的多路厚度信号进行存储之后，可以根据预设规则搜索多路厚度信号内的突变点，构成突变点集合。
请参阅图6，上述的突变点可以包括上突变点和下突变点，上述的突变点构成的集合称为突变点集合。
所述根据预设规则搜索多路厚度信号内的突变点，构成突变点集合的具体过程可以包括：
读取上变型突变点和下变型突变点的判断条件；根据判断条件从多路厚度信号内搜索突变点；将所述突变点存执突变点集合。
805、根据突变点集合确定多路厚度信号的厚度异常可疑区域；
得到突变点集合之后，可以根据突变点集合确定多路厚度信号的厚度异常可疑区域。请参阅图7，上述的厚度异常可疑区域可以包含开始下变型可疑区域、上变下变型可疑区域和上变结束型可疑区域。图7中区域1的起始点为信 号开始点，结束点为下变型突变点，称区域1为开始下变型可疑区域，类似的，称区域2为上变下变型可疑区域，区域3为上变结束型可疑区域。
806、根据厚度异常可疑区域确定多路厚度信号的厚度信号异常区域，并标记厚度信号异常区域的位置与面积；
确定多路厚度信号的厚度异常可疑区域之后，可以根据厚度异常可疑区域确定多路厚度信号的厚度异常区域，并标记厚度信号异常区域的位置与面积。
807、将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；
标记厚度信号异常区域的位置与面积之后，可以将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果。
808、对融合结果进行识别，得到识别结果；
得到融合结果之后，可以对融合结果进行识别，并得到识别结果。若融合结果为异常区域覆盖鉴伪区域，则识别该张钞票为变造币；若融合结果为异常区域的面积超过固定阈值，识别该张钞票为残损钞；否则，识别该张钞票为流通钞。
需要说明的是，上述的固定阈值为根据被测钞票和装置结构预先进行设定的，在此处不作限定。
809、根据识别结果将钞票分类并送至与类别相对应的位置。
得到识别结果之后，根据识别结果将钞票分类并送至与类别相对应的位置，例如可以将不同种类钞票传送至预定仓位，进而完成钞票识别。
下面以一个具体实例对本发明实施例的工作过程进行详细的描述：
不同币种的钞票以及不同类型的传感器件以及钞票运动速度决定了识别系统输入的差异性。设待检测钞票厚度值为THK±0.15THK，传感器能够检测的最小粘贴厚度为thk。
第一步：多路采集钞票的厚度信号；
应用霍尔传感器采集钞票厚度信号，总计M路厚度信号，每路信号的采样点数为N。
请参阅图9，为一张变造币的走钞示意图，走钞过程中传感器1和传感器 2覆盖了异物粘贴区域，传感器M没有覆盖钞票区域。各传感器采集的厚度信号的具体采集图样请参阅图10。
第二步：对多路厚度信号预处理；
此过程完成厚度信号的抽样、去噪和有效区域提取，记录预处理后的信号为S(i,j)，可以将其存储在信号处理芯片的内部存储单元中，供后续步骤使用。
针对图9中的变造币，请参阅图10，预处理过程提取到的厚度信号有效区域如图10中的黑色框线框选区域所示。
第三步：根据预设规则搜索多路厚度信号内的突变点，构成突变点集合；
相关约束条件包括：突变点跳变高度阈值T1＝ηthk和T2＝-ηthk，η∈[0.7,0.9]。
读取厚度信号数据S(i,j)，当信号采样点S(i,j)满足如下条件时，
Figure PCTCN2014087746-appb-000001
点S(i,j)为上变型突变点，令Pi(j)＝j，表示了第i路信号第j个采样点为上变型突变点，当信号采样点S(i,j)不满足上述判定条件时，令Pi(j)＝0，表示了第i路信号的第j个采样点不是上变型突变点。
当信号采样点S(i,j)满足如下条件时，
Figure PCTCN2014087746-appb-000002
点S(i,j)为下变型突变点，令Qi(j)＝-j，表示了第i路信号第j个采样点为下变型突变点，当信号采样点S(i,j)不满足上述判定条件时，令Qi(j)＝0，表示了信号i个通道的第j个采样点不是下变型突变点。
针对图9中的变造币，请参与图11，应用上述方法检测到第1路厚度信号存在两个上变型突变点和两个下变型突变点，第2路厚度信号存在一个上变型突变点和一个下变型突变点。
第四步：根据突变点集合确定多路厚度信号的厚度异常可疑区域；
记PQi为表征第i路信号的突变点标记集合，令
Figure PCTCN2014087746-appb-000003
上面突变点标记集合PQi中的非零元素表示了第i路厚度信号中突变点的位置，PQi(j)>0说明第j个点为上变型突变点，PQi(j)<0说明第j个点为下变型突变点，PQi(j)＝0说明第j个点不是突变点，下面根据突变点的位置信息确定厚度异常可疑区域的类型。
(1)开始下变型可疑区域确定；
当PQi(j)满足如下条件时，
对于
Figure PCTCN2014087746-appb-000004
有PQi(k)＝0，并且PQi(j)<0，
则存在开始下变型可疑区域，该可疑区域的起始点为Pstart(i)，长度为abs(PQi(j))-Pstart(i)；
(2)上变下变型可疑区域确定；
当PQi(j)满足如下条件时，
Figure PCTCN2014087746-appb-000005
使得
Figure PCTCN2014087746-appb-000006
k<j+m，有PQi(k)＝0，并且PQi(j)>0，PQi(j+m)<0，
则存在上变下变型可疑区域，该可疑区域的起点为abs(PQi(j))，长度为m；
(3)上变结束型可疑区域确定；
当PQi(j)满足如下条件时，
对于
Figure PCTCN2014087746-appb-000007
有PQi(k)＝0，并且PQi(j)>0，
则存在上变结束型可疑区域，该可疑区域的起始点为PQi(j)，长度为Pend(i)-PQi(j)。
针对图9中的变造币，请参阅图12，应用上述方法检测到第1路厚度信号存在两个上变下变型可疑区域，第2路厚度信号存在一个上变下变型可疑区域。
第五步：根据厚度异常可疑区域确定多路厚度信号的厚度异常区域，并标记厚度信号异常区域的位置与面积；
相关约束条件包括：异常区域厚度均值阈值TThk＝THK+η*thk，异常区域厚度标准差阈值Tstd，异常区域长度阈值Tl为1cm宽度对应的信号采样点数(此数值可根据信号采样频率和钞票走钞速度计算)；
记第i个厚度异常可疑区域的起始点为s，长度为l，计算该可疑区域厚度 平均值Thks与标准差Stds可应用下面公式计算，
Figure PCTCN2014087746-appb-000008
当平均值与标准差满足如下条件且可疑区域长度足够长时，判断该区域为厚度异常区域，即该区域满足如下条件时判断为厚度异常区域
Figure PCTCN2014087746-appb-000009
其中δ、Tstd、Tl为经验参数。
记厚度异常区域的位置为Area(k)，其面积为SArea(k)(k指该区域为钞票的第k个厚度异常区域，假设总计有N个厚度异常区域)，若厚度异常可疑区域均值和标准差特征不满足上述判定条件，则排除该可疑区域的可疑性。
针对图9中的变造币，请参阅图12，应用上述方法检测到第一路厚度信号存在两个信号异常区域Area(1)和Area(2)，第二路厚度信号存在一个信号异常区域Area(3)，其面积分别为SArea(1)，SArea(2)和SArea(3)。
第六步：将多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果并识别；
相关约束条件包括：鉴伪区域位置AreaN(此参数根据不同币种、不同面值进行设置，例如人民币100元鉴伪区域设定为水印区域和国徽区域)，厚度异常区域面积阈值TS(此数值可根据不同检测标准设置，例如ECB欧洲中央银行标准为4cm2)。
根据上面算法得到的厚度异常区域位置Area(k)和厚度异常区域面积SArea(k)，计算整张钞票的厚度异常区域位置Area和异常区域总面积SArea
Figure PCTCN2014087746-appb-000010
根据异常区域的面积和位置来给出最终的识别结果，当厚度异常区域覆盖钞票鉴伪区域AreaN时，判断该张钞票为变造币，当厚度异常区域没有覆盖鉴伪区域且厚度异常区域面积大于异常区域面积阈值TS时，判断该张钞票为残损币，否则判断该张钞票为流通钞。
针对图7中的变造币，厚度异常区域
Figure PCTCN2014087746-appb-000011
覆盖了水印区域，且异常区域面积
Figure PCTCN2014087746-appb-000012
大于异常区域面积阈值TS，判断该张钞票为变造币。
本发明实施例的方法，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
上面对本发明厚度异常钞票的识别方法的第二实施例作了详细描述，下面介绍本发明厚度异常钞票的识别系统实施例，请参阅图13，本发明实施例中厚度异常钞票的识别系统，包括：厚度传感器131、DSP芯片132、嵌入式模块133和机械运动模块134；
厚度传感器131，与DSP芯片132相连，用于采集钞票的厚度信号；
DSP芯片132，与嵌入式模块133相连，用于根据厚度信号对钞票进行分析识别，得到识别结果；
嵌入式模块133，与机械运动模块134相连，用于根据识别结果控制机械运动模块134；
机械运动模块134，用于根据嵌入式模块133的控制指令集将钞票进行分类并送至与类别相对应的位置。
本发明实施例中，厚度传感器131首先采集钞票的厚度信号，并将上述的厚度信号传输给DSP芯片132进行分析识别，DSP芯片132得到识别结果之后，将识别结果传输给嵌入式系统133，嵌入式系统133控制机械运动模块134将流通钞、残损钞和变造币传送至不同出钞仓位，实现不同种类钞票的分类。
可选地，
系统还包括存储模块135，用于存储识别结果。
可选地，
厚度传感器131为多路厚度传感器。
本发明实施例的系统，通过检测厚度信号突变点的方式，能够以更小的计算量，有效地解决因谐波信号幅值波动较大导致的正常钞票误判和因信号欠采样导致的残损钞、变造币漏检等问题。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分步骤是可以通过程序来指令相关的硬件完成，其中的程序可以存储于一种计算机可读存储介质中，上述提到的存储介质可以是只读存储器，磁盘或光盘等。
以上对本发明所提供的一种厚度异常钞票的识别方法及系统进行了详细介绍，对于本领域的一般技术人员，依据本发明实施例的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (8)

  1. 一种厚度异常钞票的识别方法，其特征在于，包括：
    多路采集钞票的厚度信号，得到多路厚度信号；
    对所述多路厚度信号预处理；
    根据预设规则搜索所述多路厚度信号内的突变点，构成突变点集合；
    根据所述突变点集合确定所述多路厚度信号的厚度异常可疑区域；
    根据所述厚度异常可疑区域确定所述多路厚度信号的厚度信号异常区域，并标记所述厚度信号异常区域的位置与面积；
    将所述多路厚度信号的厚度信号异常区域的位置与面积进行融合，得到融合结果；
    对所述融合结果进行识别，得到识别结果。
  2. 根据权利要求1所述的厚度异常钞票的识别方法，其特征在于，在步骤对所述多路厚度信号预处理之后及步骤根据预设规则搜索所述多路厚度信号内的突变点之前还包括：
    将经过预处理的多路厚度信号进行存储。
  3. 根据权利要求1所述的厚度异常钞票的识别方法，其特征在于，在步骤对所述融合结果进行识别，得到识别结果之后还包括：
    根据所述识别结果将所述钞票分类并送至与类别相对应的位置。
  4. 根据权利要求1至3中任一项所述的厚度异常钞票的识别方法，其特征在于，步骤对所述多路厚度信号预处理包括：
    对所述多路厚度信号进行抽样处理，得到抽样处理信号；
    对所述抽样处理信号进行去噪处理，得到去噪处理信号；
    对所述去噪处理信号进行有效信号区域确定，得到有效区域。
  5. 根据权利要求1至3中任一项所述的厚度异常钞票的识别方法，其特征在于，步骤所述根据预设规则搜索所述多路厚度信号内的突变点，构成突变点集合包括：
    读取上变型突变点和下变型突变点的判断条件；
    根据所述判断条件从所述多路厚度信号内搜索突变点；
    将所述突变点存执突变点集合。
  6. 一种厚度异常钞票的识别系统，其特征在于，包括：厚度传感器、DSP芯片、嵌入式模块和机械运动模块；
    所述厚度传感器，与所述DSP芯片相连，用于采集钞票的厚度信号；
    所述DSP芯片，与所述嵌入式模块相连，用于根据所述厚度信号对所述钞票进行分析识别，得到识别结果；
    所述嵌入式模块，与所述机械运动模块相连，用于根据所述识别结果控制所述机械运动模块；
    所述机械运动模块，用于根据所述嵌入式模块的控制指令集将所述钞票进行分类并送至与类别相对应的位置。
  7. 根据权利要求6所述的基于厚度信号识别的钞票识别系统，其特征在于，所述系统还包括存储模块，用于存储所述识别结果。
  8. 根据权利要求7所述的基于厚度信号识别的钞票识别系统，其特征在于，所述厚度传感器为多路厚度传感器。
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