CN116052324A - Banknote stain identification and fake detection method - Google Patents
Banknote stain identification and fake detection method Download PDFInfo
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- CN116052324A CN116052324A CN202211719104.9A CN202211719104A CN116052324A CN 116052324 A CN116052324 A CN 116052324A CN 202211719104 A CN202211719104 A CN 202211719104A CN 116052324 A CN116052324 A CN 116052324A
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- 238000001514 detection method Methods 0.000 title claims description 19
- 238000000034 method Methods 0.000 claims abstract description 12
- 238000012163 sequencing technique Methods 0.000 claims abstract description 4
- 238000011109 contamination Methods 0.000 claims 3
- 238000005516 engineering process Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- PCHJSUWPFVWCPO-UHFFFAOYSA-N gold Chemical compound [Au] PCHJSUWPFVWCPO-UHFFFAOYSA-N 0.000 description 1
- 239000010931 gold Substances 0.000 description 1
- 229910052737 gold Inorganic materials 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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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
- G07D7/20—Testing patterns thereon
- G07D7/2016—Testing patterns thereon using feature extraction, e.g. segmentation, edge detection or Hough-transformation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
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- Computer Vision & Pattern Recognition (AREA)
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- Theoretical Computer Science (AREA)
- Inspection Of Paper Currency And Valuable Securities (AREA)
Abstract
The invention relates to a method for identifying and checking false stains on bank notes, which comprises the following steps: 1) Acquiring gray level images of brand new banknotes; 2) Dividing a gray image into n identical areas, wherein each area corresponds to a position serial number, and accumulating gray values of all pixel points in each area to obtain n gray data; 3) Sequencing n areas according to gray data from large to small, then giving gray serial numbers to each area, setting gray serial numbers of 1-n/2-1 as white areas, and setting gray serial numbers of n/2-n as black areas; 4) Storing the gray data, the position serial number and the gray serial number as image template data of the banknote; 5) Acquiring a sample banknote of the same version of denomination, and acquiring gray data of the sample banknote by using the same method of the steps 1) and 2); 6) The gray data of the sample bank note is sequenced, n areas in the sample bank note and the brand new bank note are compared according to the position serial numbers, and whether the bank note has dirt or not is judged according to the gray serial number of each area in the sample bank note.
Description
Technical Field
The invention belongs to the technical field of banknote recognition, and relates to a banknote stain recognition and fake detection method.
Background
The banknote counter is an electromechanical integrated device for automatically counting the number of banknotes and integrates the functions of counting and distinguishing counterfeit banknotes.
Due to the huge domestic cash flow scale, cash handling work of enterprises and institutions and financial institutions is heavy, and a cash counter becomes an indispensable device. With the development of printing technology, copying technology and electronic scanning technology, the manufacturing level of counterfeit money is higher and higher, and the counterfeit identification performance of the banknote counter must be continuously improved. Since the issuance of the gold mark of the RMB banknote counter, a new development of the banknote counter is brought, and the original detection technology is urgently needed to be perfected.
In the using and circulating process of the banknote, the surface of the banknote is inevitably stained and the like, the banknote counting speed of the banknote counter is high, and the counterfeit detection is realized, so that a stain recognition algorithm is also quick. This is particularly important for systems employing image recognition to detect fraud, how to quickly and effectively remove and separate the identified banknote stains.
The existing spot recognition method of the banknote counter generally aims at a mean value algorithm and a threshold value algorithm of a certain specific area of an image or is a gradient algorithm, so that the algorithms are difficult to rapidly recognize the spots of the whole banknote, and the spot detection requirement of the banknote counter cannot be met.
Disclosure of Invention
In order to solve the technical problems, the invention aims to provide a banknote stain identification and fake detection method which can effectively and rapidly identify banknote stains.
The invention provides a banknote stain identification and fake detection method, which comprises the following steps:
1) Acquiring gray level images of brand new banknotes;
2) Dividing a gray image into n identical areas, wherein each area corresponds to one position number 1-n, and accumulating gray values of all pixel points in each area to obtain n gray data;
3) Sequencing n areas from large to small according to gray data, then giving each area a gray sequence number, and setting black and white attribute of each area according to the gray sequence number;
4) Saving the gray data, the position serial number and the gray serial number as image template data of the banknote;
5) Acquiring a sample banknote of the same version of denomination, and acquiring gray data of the sample banknote by using the same method of steps 1) and 2);
6) The gray data of the sample bank note is sequenced, n rectangular areas in the sample bank note and the brand new bank note are compared in a one-to-one correspondence mode according to the position serial numbers, and whether the bank note has dirt is judged according to the gray serial numbers of all the rectangular areas in the sample bank note.
In the banknote stain recognition and forgery detection method of the present invention, the gradation image in step 1) is a banknote gradation image obtained in actual width and height among the whole white light image of the banknote.
In the banknote stain identification and false detection method of the invention, the step 2) specifically comprises the following steps:
dividing the gray image into n rectangular areas with the same size; each rectangular area is sequentially given a position number from left to right starting from the first row of rectangular areas from top to bottom.
In the banknote stain identification and false detection method of the invention, the step 3) specifically comprises the following steps:
setting gray scale number
The region of (2) is a white region, and the gray number is +.>
Is a black region.
In the banknote stain identification and false detection method of the invention, the step 6) judges banknote oil stains according to the gray serial numbers of all areas in the sample banknote, specifically comprises the following steps:
if the gray sequence number of the template data is located at the same position
After the gray data of the sample bank note are ordered, the gray serial number is +.>
Then black stains are considered; if the gray sequence number of the template data is located +.>
After the gray data of the sample bank note are ordered, the gray serial number is +.>
White stains are considered.
The banknote stain identification and fake detection method has at least the following beneficial effects:
1. the banknote stain identification method provided by the invention adopts comparison operation to the gray serial numbers according to the position sequence, so that banknote stains can be rapidly and effectively judged.
2. The operation object of the invention is only to the pixel value accumulated value of the image, the consumed time and resource are very little, the invention is very beneficial to the fake detection system of the whole banknote counter, and the method can be also applicable to other banknote with similar characteristics.
Drawings
Fig. 1 is a flow chart of a banknote deposit machine identification and counterfeit detection method of the present invention.
Detailed Description
As shown in fig. 1, the banknote stain identification and false detection method of the invention comprises the following steps:
1) Acquiring gray level images of brand new banknotes;
in the specific implementation, the bill identifier acquires a white light image of the bill in the bill counting process, and the gray level image is a bill gray level image acquired in the actual width and height in the whole white light image of the bill.
2) Dividing a gray image into n identical areas, wherein each area corresponds to one position number 1-n, and accumulating gray values of all pixel points in each area to obtain n gray data;
in specific implementation, dividing a gray image into n rectangular areas with the same size; each rectangular area is sequentially given a position number from left to right starting from the first row of rectangular areas from top to bottom.
3) Sequencing n areas from large to small according to gray data, then giving each area a gray sequence number, and setting black and white attribute of each area according to the gray sequence number;
the gray value shows the black-and-white attribute of the image, the larger the gray value is, the more the image attribute is white, and the gray value is 255 is white; the smaller the gray value, the more black the image attribute appears, and a gray value of 0 is black.
In the specific implementation, the gray serial number is set as
The region of (2) is a white region, and the gray number is +.>
Is a black region.
4) Saving the gray data, the position serial number and the gray serial number as image template data of the banknote;
5) Acquiring a sample banknote of the same version of denomination, and acquiring gray data of the sample banknote by using the same method of steps 1) and 2);
6) The gray data of the sample bank note is sequenced, n rectangular areas in the sample bank note and the brand new bank note are compared in a one-to-one correspondence mode according to the position serial numbers, and whether the bank note has dirt is judged according to the gray serial numbers of all the rectangular areas in the sample bank note.
In specific implementation, the banknote oil stain is judged according to the gray serial number of each area in the sample banknote, specifically:
if the gray sequence number of the template data is located at the same position
After the gray data of the sample bank note are ordered, the gray serial number is +.>
Then black stains are considered; if the gray sequence number of the template data is located +.>
After the gray data of the sample bank note are ordered, the gray serial number is +.>
White stains are considered.
The foregoing description of the preferred embodiments of the invention is not intended to limit the scope of the invention, but rather to enable any modification, equivalent replacement, improvement or the like to be made without departing from the spirit and principles of the invention.
Claims (5)
1. A method for identifying and checking false stains on a banknote, which is characterized by comprising the following steps:
1) Acquiring gray level images of brand new banknotes;
2) Dividing a gray image into n identical areas, wherein each area corresponds to one position number 1-n, and accumulating gray values of all pixel points in each area to obtain n gray data;
3) Sequencing n areas from large to small according to gray data, then giving each area a gray sequence number, and setting black and white attribute of each area according to the gray sequence number;
4) Saving the gray data, the position serial number and the gray serial number as image template data of the banknote;
5) Acquiring a sample banknote of the same version of denomination, and acquiring gray data of the sample banknote by using the same method of steps 1) and 2);
6) The gray data of the sample bank note is sequenced, n rectangular areas in the sample bank note and the brand new bank note are compared in a one-to-one correspondence mode according to the position serial numbers, and whether the bank note has dirt is judged according to the gray serial numbers of all the rectangular areas in the sample bank note.
2. The method of claim 1, wherein the gray image in step 1) is a gray image of a bill obtained in actual width and height in a white light image of the whole bill.
3. A banknote contamination identification and counterfeit detection method as set forth in claim 1, wherein: the step 2) is specifically as follows:
dividing the gray image into n rectangular areas with the same size; each rectangular area is sequentially given a position number from left to right starting from the first row of rectangular areas from top to bottom.
4. The banknote contamination identification and counterfeit detection method according to claim 1, wherein step 3) specifically comprises:
setting gray scale number
The region of (2) is a white region, and the gray number is +.>
Is a black region.
5. A banknote contamination identification and counterfeit detection method as set forth in claim 1, wherein: step 6) judging the oil stain of the banknote according to the gray serial number of each area in the sample banknote, specifically:
if the gray sequence number of the template data is located at the same position
After the gray data of the sample bank note are ordered, the gray serial number is +.>
Then black stains are considered; if the gray sequence number of the template data is located +.>
After the gray data of the sample bank note are ordered, the gray serial number is +.>
White stains are considered. />
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211719104.9A CN116052324A (en) | 2022-12-30 | 2022-12-30 | Banknote stain identification and fake detection method |
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| CN202211719104.9A CN116052324A (en) | 2022-12-30 | 2022-12-30 | Banknote stain identification and fake detection method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118038366A (en) * | 2024-02-20 | 2024-05-14 | 青岛法牧机械有限公司 | Intelligent monitoring system and method for pig farm cultivation |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118038366A (en) * | 2024-02-20 | 2024-05-14 | 青岛法牧机械有限公司 | Intelligent monitoring system and method for pig farm cultivation |
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