CN107331026B - Paper money identification method and device - Google Patents
Paper money identification method and device Download PDFInfo
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- CN107331026B CN107331026B CN201710447999.8A CN201710447999A CN107331026B CN 107331026 B CN107331026 B CN 107331026B CN 201710447999 A CN201710447999 A CN 201710447999A CN 107331026 B CN107331026 B CN 107331026B
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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
- G06V10/267—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 by performing operations on regions, e.g. growing, shrinking or watersheds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/14—Image acquisition
- G06V30/148—Segmentation of character regions
- G06V30/158—Segmentation of character regions using character size, text spacings or pitch estimation
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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
- G07D7/2075—Setting acceptance levels or parameters
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Abstract
the invention belongs to the field of financial machines and tools, and particularly relates to a paper money identification method and device. The method comprises the following steps: firstly, extracting an area where a crown word number of a paper currency to be recognized is located from a first image, then dividing the area where the crown word number of the paper currency to be recognized is located into a first sub-area where a first character is located and a second sub-area where a second character is located, extracting a first pixel group occupied by the first character from the first sub-area and extracting a second pixel group occupied by the second character from the second sub-area respectively, finally calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group respectively, and judging the authenticity of the paper currency to be recognized according to the first average gray value and the second average gray value. The invention fully utilizes the special optical property of the crown word number and can greatly improve the accuracy of identifying the crown word number.
Description
Technical Field
The invention belongs to the field of financial machines and tools, and particularly relates to a paper money identification method and device.
Background
the paper money identification is one of the basic functions of various ATM machines, and the main principle is to utilize various marks arranged on the paper money to judge the truth of the paper money so as to prevent abnormal paper money from flowing into the market and influencing the normal financial order.
The existing paper money identification technology generally collects paper money images by selecting green visible light in a visible light wave band, and processes and analyzes the collected images so as to judge the authenticity of the paper money.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for identifying paper currency to solve the problem of low accuracy in identifying a crown word number in the prior art.
a first aspect of an embodiment of the present invention provides a banknote recognition method, which may include:
Extracting an area where a crown word number of the paper money to be identified is located from a first image, wherein the first image is an image displayed by the paper money to be identified under the irradiation of visible light in a red waveband;
dividing the region where the crown word number of the paper money to be recognized is located into a first sub-region where a first character is located and a second sub-region where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized;
extracting a first pixel group occupied by the first character from the first sub-area;
extracting a second pixel group occupied by the second character from the second sub-area;
Respectively calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group;
if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value, judging that the paper money to be identified is a genuine money, wherein the first threshold value is a positive number;
And if the difference value obtained by subtracting the second average gray value from the first average gray value is smaller than or equal to the first threshold value, judging the paper money to be identified as abnormal paper money.
Further, the dividing the region where the crown word number of the paper money to be recognized is located into a first sub-region where the first character is located and a second sub-region where the second character is located includes:
acquiring first lengths of areas where the first four characters in the standard serial number are located in the character arrangement direction, wherein the standard serial number is a preset serial number of standard paper money corresponding to the paper money to be recognized;
acquiring second lengths of areas where the last six characters in the standard crown word size are located in the character arrangement direction;
calculating a first ratio of the first length to the second length;
and sequentially dividing the region where the crown word number of the paper money to be recognized is located into the first sub-region and the second sub-region in the character arrangement direction, so that a second ratio is equal to the first ratio, wherein the second ratio is the ratio of the length of the first sub-region in the character arrangement direction to the length of the second sub-region in the character arrangement direction.
Further, the extracting the first pixel group occupied by the first character from the first sub-area includes:
Carrying out binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region;
extracting the first pixel group from the first sub-area according to the binarization image of the first sub-area;
The extracting of the second pixel group occupied by the second character from the second sub-area includes:
carrying out binarization processing on the image of the second sub-area to obtain a binarized image of the second sub-area;
and extracting the second pixel group from the second sub-area according to the binarized image of the second sub-area.
further, the binarizing the image of the first sub-region includes:
Carrying out binarization processing on the image of the first sub-region by using an adaptive threshold value binarization algorithm;
The binarization processing of the image of the second sub-area comprises:
and carrying out binarization processing on the image of the second sub-area by using an adaptive threshold value binarization algorithm.
Further, after determining that the banknote to be recognized is a genuine banknote, the banknote recognition method further includes:
Respectively acquiring a first sub-image presented by the first sub-area under the irradiation of infrared light and a second sub-image presented by the second sub-area under the irradiation of the infrared light;
Judging whether visible characters exist in the first sub-image and whether visible characters exist in the second sub-image;
If the visible characters do not exist in the first sub-image and the visible characters exist in the second sub-image, the fact that the paper money to be recognized is true is determined, and the judgment result that the paper money to be recognized is the true money is verified;
and if the visible characters exist in the first sub-image or the second sub-image, determining that the judgment result that the paper money to be recognized is the true money is verified to be false.
Further, the determining whether there are visible characters in the first sub-image and whether there are visible characters in the second sub-image comprises:
Respectively calculating a first variance of the pixel group gray value of the first sub-image and a second variance of the pixel group gray value of the second sub-image;
If the difference value of subtracting the first variance from the second variance is larger than a preset second threshold value, determining that no visible character exists in the first sub-image and no visible character exists in the second sub-image, wherein the second threshold value is a positive number;
and if the difference value of the second variance minus the first variance is less than or equal to the second threshold, determining that visible characters exist in the first sub-image or visible characters do not exist in the second sub-image.
A second aspect of an embodiment of the present invention provides a banknote recognition apparatus, which may include:
the system comprises a crown word number extraction module, a first image processing module and a second image processing module, wherein the crown word number extraction module is used for extracting an area where a crown word number of a paper currency to be identified is located from a first image, and the first image is an image displayed by the paper currency to be identified under the irradiation of visible light in a red wave band;
the area dividing module is used for dividing the area where the crown word number of the paper money to be recognized is located into a first sub-area where a first character is located and a second sub-area where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized;
A first pixel group extraction module, configured to extract a first pixel group occupied by the first character from the first sub-region;
the second pixel group extraction module is used for extracting a second pixel group occupied by the second character from the second sub-area;
The first average gray value calculation module is used for calculating a first average gray value of the first pixel group;
A second average gray value calculation module for calculating a second average gray value of the second pixel group;
The first judging module is used for judging the paper money to be identified as a genuine paper money if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value;
And the second judging module is used for judging that the paper money to be identified is abnormal money if the difference value obtained by subtracting the second average gray value from the first average gray value is less than or equal to the first threshold value.
further, the region dividing module includes:
the first length obtaining unit is used for obtaining the first length of an area where the first four characters in the standard serial number are located in the character arrangement direction, and the standard serial number is the preset serial number of the standard paper currency corresponding to the paper currency to be identified;
A second length obtaining unit, configured to obtain second lengths of areas where the last six characters in the standard prefix number are located in the character arrangement direction;
a first ratio calculation unit for calculating a first ratio of the first length to the second length;
And the area dividing unit is used for sequentially dividing the area where the crown word number of the paper money to be recognized is located into the first sub-area and the second sub-area in the character arrangement direction, so that a second ratio is equal to a first ratio, and the second ratio is the ratio of the length of the first sub-area in the character arrangement direction to the length of the second sub-area in the character arrangement direction.
Further, the first pixel group extraction module includes:
the first processing unit is used for carrying out binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region;
a first extraction unit configured to extract the first pixel group from the first sub-region based on a binarized image of the first sub-region;
the second pixel group extraction module includes:
the second processing unit is used for carrying out binarization processing on the image of the second sub-area to obtain a binarized image of the second sub-area;
A second extraction unit configured to extract the second pixel group from the second sub-region based on the binarized image of the second sub-region.
Further, the first processing unit includes:
the first processing subunit is used for carrying out binarization processing on the image of the first sub-region by using an adaptive threshold value binarization algorithm;
The second processing unit includes:
And the second processing subunit is used for performing binarization processing on the image of the second sub-region by using an adaptive threshold value binarization algorithm.
further, the paper money discriminating apparatus further includes:
The first sub-image acquisition module is used for acquiring a first sub-image presented by the first sub-area under the irradiation of infrared light;
the second sub-image acquisition module is used for acquiring a second sub-image presented by the second sub-area under the irradiation of the infrared light;
the visible character judgment module is used for judging whether visible characters exist in the first sub-image and whether visible characters exist in the second sub-image;
the first checking module is used for determining that the judgment result that the paper money to be identified is the true paper money is checked to be true if the visible characters do not exist in the first sub-image and the visible characters exist in the second sub-image;
And the second checking module is used for determining that the judgment result that the paper money to be recognized is the true money is checked to be false if the visible characters exist in the first sub-image or the visible characters do not exist in the second sub-image.
further, the visible character judgment module includes:
a first variance calculating unit for calculating a first variance of the pixel group gradation values of the first sub-image;
a second variance calculating unit for calculating a second variance of the pixel group gradation value of the second sub-image;
A first determining unit, configured to determine that there is no visible character in the first sub-image and there is a visible character in the second sub-image if a difference between the second variance and the first variance is greater than a preset second threshold, where the second threshold is a positive number;
A second determining unit, configured to determine that there is a visible character in the first sub-image or no visible character in the second sub-image if a difference between the second variance and the first variance is smaller than or equal to the second threshold.
a third aspect of an embodiment of the present invention provides a banknote recognition terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the above banknote recognition methods when executing the computer program.
a fourth aspect of the embodiments of the present invention provides a computer-readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the steps of any one of the above banknote recognition methods.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: the method comprises the steps of extracting an area where a crown word number of the paper money to be identified is located from a first image, wherein the first image is an image displayed by the paper money to be identified under the irradiation of visible light in a red wave band; dividing the region where the crown word number of the paper money to be recognized is located into a first sub-region where a first character is located and a second sub-region where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized; extracting a first pixel group occupied by the first character from the first sub-area; extracting a second pixel group occupied by the second character from the second sub-area; respectively calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group; if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value, judging the paper money to be identified as a genuine paper money; and if the difference value obtained by subtracting the second average gray value from the first average gray value is smaller than or equal to the first threshold value, judging the paper money to be identified as abnormal paper money. Because the first four characters of the serial number of the RMB are red and the last six characters are black, if the green wave band visible light in the prior art is adopted, all the ten serial number characters are black with approximate gray values, and the identification accuracy is low, while under the irradiation of the red wave band visible light adopted by the invention, the gray values of the first four characters are obviously lighter than those of the last six characters, and the truth and falseness of the paper money to be identified can be determined according to the average gray values of the two characters.
drawings
in order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
FIG. 1 is a schematic flow chart of a banknote recognition method according to an embodiment of the present invention;
Fig. 2 is a schematic flow chart of the division of the prefix number sub-regions according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a banknote recognition method according to a second embodiment of the present invention;
Fig. 4 is a schematic block diagram of a banknote recognition apparatus according to a third embodiment of the present invention;
fig. 5 is a schematic block diagram of a banknote recognition terminal device provided in an embodiment of the present invention.
Detailed Description
in order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
As shown in fig. 1, which is a schematic flow chart of a banknote identifying method according to an embodiment of the present invention, the method may include:
And S101, extracting the area where the crown word number of the paper money to be identified is located from the first image.
The first Image is an Image displayed by the paper money to be identified under the irradiation of visible light with a red waveband emitted by a Contact Image Sensor (CIS). In this embodiment, the banknotes to be identified are the fifth current universal set of rmb.
the serial number is a series of codes on the lower left of the genuine RMB, the serial number of each genuine RMB is unique, wherein, the serial number is two or three English letters printed on the paper money for marking the printing batch, and the serial number is arranged and printed by a banknote printing factory according to a certain rule; the number is an Arabic numeral serial number printed behind the crown word and used for indicating the arrangement sequence of each banknote in the same crown word batch.
firstly, a possible area with the crown word number on the first image is intercepted, and the binarization processing is carried out on the intercepted gray level image of the possible area to obtain a binary image of the possible area.
the possible region is a region where the crown word number is likely to appear on the image. In this embodiment, the possible area may be preset according to historical statistical data. In order to reduce the amount of computation or processing, firstly, a possible region is intercepted, and binarization processing is performed on the gray level image of the possible region, wherein the gray level value of a character with a prefix number in the gray level image of the region after binarization processing is 1, and the gray level value of the rest regions is 0.
secondly, on the binary image of the possible area, moving a first moving window line by line, acquiring the pixel accumulated value of the area where the current first moving window is located, and when the pixel accumulated value of the first moving window is the maximum value, determining that the first line of the area where the first moving window is located is the initial line of the area where the prefix number is located.
in this embodiment, the width of the possible area is W, the height is H, the width of the area where the known crown word number is located is NW (NW < W), the height of the area where the known crown word number is located is NH (NH < H), the first moving window is a window formed according to the height of the area where the known crown word number is located and the width of the possible area, that is, a window with a size of W × NH is selected, the first moving window is moved line by line, the pixel accumulated value of the area where the current first moving window is located is obtained, and when the pixel accumulated value of the first moving window is the maximum value, the first line of the area where the first moving window is the start line of the area where the crown word number is located.
and thirdly, moving the second moving window column by column, acquiring the pixel accumulated value of the area where the current second moving window is located, and determining that the first column of the area where the second moving window is located is the initial column of the area where the prefix number is located when the pixel accumulated value of the second moving window is the maximum value.
in this embodiment, the width of the possible area is W, the height is H, the width of the area where the known crown word number is located is NW (NW < W), the height of the area where the known crown word number is located is NH (NH < H), the second moving window is a window formed according to the height and the width of the area where the known crown word number is located, that is, a window with a size of NW × NH is selected, the second moving window is moved column by column, the pixel accumulation value of the area where the current second moving window is located is obtained, and when the pixel accumulation value of the second moving window is the maximum value, the first column of the area where the second moving window is located is the start column of the area where the crown word number is located.
And finally, extracting the area where the crown word number of the paper money to be identified is located according to the initial row, the initial column and the height and width of the area where the known crown word number is located.
step S102, dividing the area where the crown word number of the paper money to be identified is located into a first sub-area where the first character is located and a second sub-area where the second character is located.
The first characters are the first four characters in the crown word number of the paper money to be recognized, and the second characters are the last six characters in the crown word number of the paper money to be recognized.
preferably, as shown in fig. 2, step S102 may specifically include:
step S1021, acquiring a first length of an area where the first four characters in the standard prefix number are located in the character arrangement direction.
The standard serial number is a preset serial number of the standard paper currency corresponding to the paper currency to be identified, the current universal fifth set of RMB includes paper currencies with face values of 1 yuan, 5 yuan, 10 yuan, 20 yuan, 50 yuan and 100 yuan, and for each type of paper currency, the serial number of the standard paper currency of the type is acquired in advance so as to provide reference for various types of paper currencies to be identified.
in the fifth current universal set of rmb, the first four characters in the prefix number are red.
And determining the rightmost pixel point of the fourth character and the leftmost pixel point of the fifth character of the crown word number, and determining the midpoint pixel point between the two pixel points according to the pixel points. If the rightmost pixel point of the fourth character is not unique, one pixel point can be selected arbitrarily; and if the leftmost pixel point of the fifth character is not unique, selecting one pixel point arbitrarily.
and determining the leftmost pixel point of the first character of the crown word number, and measuring the projection length of the connection line of the pixel point and the midpoint pixel point in the character arrangement direction, wherein the projection length is the first length. If the leftmost pixel point of the first character is not unique, one pixel point can be selected arbitrarily.
Step S1022, a second length of the area where the last six characters in the standard prefix number are located in the character arrangement direction is obtained.
In the fifth current universal set of rmb, the last six characters in the crown size are black.
and determining the rightmost pixel point of the tenth character of the crown word number, and measuring the projection length of the connecting line of the pixel point and the midpoint pixel point in the character arrangement direction, wherein the projection length is the second length. If the rightmost pixel point of the tenth character is not unique, one pixel point can be selected arbitrarily.
in step S1023, a first ratio of the first length to the second length is calculated.
step S1024, the area where the crown word number of the paper money to be recognized is located is sequentially divided into the first sub-area and the second sub-area in the character arrangement direction, and the second ratio is equal to the first ratio.
the second ratio is a ratio of a length of the first sub-area in the character arrangement direction to a length of the second sub-area in the character arrangement direction.
the first sub-area thus divided is an area occupied by red characters, and the second sub-area is an area occupied by black characters.
Step S103, extracting a first pixel group occupied by the first character from the first sub-area.
specifically, step S103 may include:
and carrying out binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region.
in this embodiment, it is preferable to perform binarization processing on the image of the first sub-region by using an adaptive threshold binarization algorithm. For example, the image may be divided into smaller blocks, a histogram may be calculated for each block separately, and a threshold may be calculated for each block based on the peak of each histogram. And the threshold value of each pixel point is obtained by interpolation according to the threshold values of the adjacent blocks.
it should be noted that other binarization processing methods may also be selected according to actual needs, which is not specifically limited in this embodiment.
extracting the first pixel group from the first sub-area according to the binarization image of the first sub-area;
If the points larger than the threshold value are set to be black and the points smaller than the threshold value are set to be white in the binarization process, a set formed by pixel points corresponding to the black pixel points in the binarization image in the first sub-area is the first pixel group; if the point larger than the threshold value is set to be white and the point smaller than the threshold value is set to be black in the binarization process, a set formed by pixel points corresponding to the white pixel points in the binarization image in the first sub-area is the first pixel group.
and step S104, extracting a second pixel group occupied by the second character from the second sub-area.
specifically, step S104 may include:
And carrying out binarization processing on the image of the second sub-area to obtain a binarized image of the second sub-area.
In this embodiment, it is preferable to perform binarization processing on the image of the first sub-region by using an adaptive threshold binarization algorithm. For example, the image may be divided into smaller blocks, a histogram may be calculated for each block separately, and a threshold may be calculated for each block based on the peak of each histogram. And the threshold value of each pixel point is obtained by interpolation according to the threshold values of the adjacent blocks.
it should be noted that other binarization processing methods may also be selected according to actual needs, which is not specifically limited in this embodiment.
extracting the second pixel group from the second sub-area according to the binarized image of the second sub-area;
If the points larger than the threshold value are set to be black and the points smaller than the threshold value are set to be white in the binarization process, a set formed by pixel points corresponding to the black pixel points in the binarization image in the second sub-area is the second pixel group; if the point larger than the threshold value is set to be white and the point smaller than the threshold value is set to be black in the binarization process, the set formed by the pixel points corresponding to the white pixel points in the binarization image in the second sub-area is the second pixel group.
step S105, respectively calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group.
step S106, judging whether the difference value of the first average gray value minus the second average gray value is larger than a preset first threshold value;
The first threshold value is a positive number, and the value of the first threshold value can be set according to the statistical result of the standard paper money;
If the difference between the first average gray value and the second average gray value is greater than a preset first threshold, step S107 is executed, and if the difference between the first average gray value and the second average gray value is less than or equal to the first threshold, step S108 is executed.
and step S107, judging the paper money to be identified as genuine paper money.
and step S108, judging the paper money to be identified as abnormal paper money.
In summary, in the embodiment of the present disclosure, an area where a crown word number of a banknote to be identified is located is extracted from a first image, where the first image is an image of the banknote to be identified under the irradiation of visible light in a red waveband; dividing the region where the crown word number of the paper money to be recognized is located into a first sub-region where a first character is located and a second sub-region where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized; extracting a first pixel group occupied by the first character from the first sub-area; extracting a second pixel group occupied by the second character from the second sub-area; respectively calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group; if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value, judging the paper money to be identified as a genuine paper money; and if the difference value obtained by subtracting the second average gray value from the first average gray value is smaller than or equal to the first threshold value, judging the paper money to be identified as abnormal paper money. Because the first four characters of the serial number of the RMB are red and the last six characters are black, if the green wave band visible light in the prior art is adopted, all the ten serial number characters are black with approximate gray values, and the identification accuracy is low, while under the irradiation of the red wave band visible light adopted by the invention, the gray values of the first four characters are obviously lighter than those of the last six characters, and the truth and falseness of the paper money to be identified can be determined according to the average gray values of the two characters.
Example two:
as shown in fig. 3, which is a schematic flowchart of a banknote identifying method according to an embodiment of the present invention, the method may include:
Step S301, extracting the area where the crown word number of the paper money to be identified is located from the first image.
Step S302, dividing the area where the crown word number of the paper money to be identified is located into a first sub-area where the first character is located and a second sub-area where the second character is located.
Step S303, extracting a first pixel group occupied by the first character from the first sub-region.
Step S304, extracting a second pixel group occupied by the second character from the second sub-area.
step S305, respectively calculating a first average gray-scale value of the first pixel group and a second average gray-scale value of the second pixel group.
Step S301 to step S305 are the same as step S101 to step S105 in the first embodiment, and specific reference may be made to the description in the first embodiment, which is not repeated herein.
step S306, judging whether the first average gray value is larger than the second average gray value;
if the difference between the first average gray value and the second average gray value is greater than a preset first threshold, step S307 is executed, and if the difference between the first average gray value and the second average gray value is less than or equal to the first threshold, step S308 is executed.
and step S307, judging the paper money to be identified as genuine paper money. After step S307, steps S309 to S311 are executed.
and step S308, judging the paper money to be identified as abnormal paper money.
step S309, respectively acquiring a first sub-image presented by the first sub-area under the irradiation of the infrared light and a second sub-image presented by the second sub-area under the irradiation of the infrared light.
step S310, judging whether visible characters exist in the first sub-image and whether visible characters exist in the second sub-image;
specifically, the determination process of step S310 may include:
Respectively calculating a first variance of the pixel group gray value of the first sub-image and a second variance of the pixel group gray value of the second sub-image;
If the difference value obtained by subtracting the first variance from the second variance is larger than a preset second threshold value, determining that no visible character exists in the first sub-image and a visible character exists in the second sub-image, wherein the second threshold value is a positive number and can be set according to a statistical result of standard paper money;
and if the difference value of the second variance minus the first variance is less than or equal to the second threshold, determining that visible characters exist in the first sub-image or visible characters do not exist in the second sub-image.
if there is no visible character in the first sub-image and there is a visible character in the second sub-image, step S311 is performed, and if there is a visible character in the first sub-image or there is no visible character in the second sub-image, step S312 is performed.
and step S311, determining that the to-be-identified paper money is true, and verifying the judgment result that the to-be-identified paper money is true.
and step S312, determining that the judgment result that the paper money to be identified is true is verified to be false.
in summary, in this embodiment, on the basis of the first embodiment, a first sub-image presented by the first sub-area under the irradiation of infrared light and a second sub-image presented by the second sub-area under the irradiation of infrared light are respectively obtained, a first variance of a pixel group gray scale value of the first sub-image and a second variance of a pixel group gray scale value of the second sub-image are respectively calculated, if a difference obtained by subtracting the first variance from the second variance is greater than a preset second threshold, it is determined that the determination result that the banknote to be identified is a true banknote is checked, and if a difference obtained by subtracting the first variance from the second variance is less than or equal to the second threshold, it is determined that the determination result that the banknote to be identified is a true banknote is checked. Because the first four characters of the serial number of the RMB are red and the last six characters are black, under the irradiation of the infrared light adopted by the invention, the first four characters are basically invisible, the gray value is not greatly different from the gray value of the background, namely the variance is smaller, while the last six characters are visible, the gray value is greatly different from the gray value of the background, namely the variance is larger, and the result in the first embodiment can be checked accordingly.
example three:
as shown in fig. 4, which is a schematic block diagram of a banknote recognition apparatus according to an embodiment of the present invention, the apparatus may include:
the crown word number extraction module 401 is configured to extract an area where a crown word number of a banknote to be identified is located from a first image, where the first image is an image of the banknote to be identified under the irradiation of visible light in a red waveband;
The region dividing module 402 is configured to divide a region where the crown word number of the banknote to be recognized is located into a first sub-region where a first character is located and a second sub-region where a second character is located, where the first character is the first four characters in the crown word number of the banknote to be recognized, and the second character is the last six characters in the crown word number of the banknote to be recognized;
a first pixel group extracting module 403, configured to extract a first pixel group occupied by the first character from the first sub-region;
a second pixel group extracting module 404, configured to extract a second pixel group occupied by the second character from the second sub-region;
A first average gray value calculating module 405, configured to calculate a first average gray value of the first pixel group;
a second average gray value calculating module 406, configured to calculate a second average gray value of the second pixel group;
A first determining module 407, configured to determine that the banknote to be identified is a genuine banknote if a difference between the first average gray value and the second average gray value is greater than a preset first threshold, where the first threshold is a positive number;
And a second determining module 408, configured to determine that the banknote to be identified is an abnormal banknote if a difference between the first average gray value and the second average gray value is smaller than or equal to the first threshold.
Further, the region dividing module 402 includes:
the first length obtaining unit 4021 is configured to obtain a first length of an area where the first four characters in a standard serial number are located in a character arrangement direction, where the standard serial number is a preset serial number of a standard banknote corresponding to the banknote to be recognized;
A second length obtaining unit 4022, configured to obtain second lengths of regions where the last six characters in the standard prefix number are located in the character arrangement direction;
a first ratio calculating unit 4023, configured to calculate a first ratio between the first length and the second length;
the region dividing unit 4024 is configured to sequentially divide a region where the crown word number of the banknote to be recognized is located into the first sub region and the second sub region in the character arrangement direction, so that a second ratio is equal to a first ratio, where the second ratio is a ratio of a length of the first sub region in the character arrangement direction to a length of the second sub region in the character arrangement direction.
Further, the first pixel group extraction module 403 includes:
A first processing unit 4031, configured to perform binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region;
a first extraction unit 4032, configured to extract the first pixel group from the first sub-region according to the binarized image of the first sub-region;
the second pixel group extraction module 404 includes:
a second processing unit 4041, configured to perform binarization processing on the image of the second sub-region to obtain a binarized image of the second sub-region;
A second extraction unit 4042, configured to extract the second pixel group from the second sub-region according to the binarized image of the second sub-region.
Further, the first processing unit 4031 includes:
a first processing subunit 40311, configured to perform binarization processing on the image of the first sub-region by using an adaptive threshold binarization algorithm;
the second processing unit includes a first processing unit 4041:
A second processing sub-unit 40411, configured to perform binarization processing on the image of the second sub-region by using an adaptive threshold binarization algorithm.
further, the paper money discriminating apparatus further includes:
a first sub-image obtaining module 409, configured to obtain a first sub-image presented by the first sub-area under the irradiation of infrared light;
a second sub-image obtaining module 410, configured to obtain a second sub-image presented by the second sub-area under the irradiation of the infrared light;
A visible character determining module 411, configured to determine whether a visible character exists in the first sub-image and whether a visible character exists in the second sub-image;
The first checking module 412 is configured to determine that the determination result that the banknote to be recognized is a genuine banknote is checked to be true if there is no visible character in the first sub-image and there is a visible character in the second sub-image;
the second checking module 413 is configured to determine that the determination result that the banknote to be recognized is a true banknote is checked to be false if a visible character exists in the first sub-image or a visible character does not exist in the second sub-image.
further, the visible character determination module 411 includes:
A first square difference calculating unit 4111, configured to calculate a first square difference between the gray-scale values of the pixel groups of the first sub-image;
A second variance calculating unit 4112, configured to calculate a second variance of the gray-scale values of the pixel group of the second sub-image;
A first determining unit 4113, configured to determine that there is no visible character in the first sub-image and there is a visible character in the second sub-image if a difference between the second variance and the first variance is greater than a preset second threshold, where the second threshold is a positive number;
a second determining unit 4114, configured to determine that there is a visible character in the first sub-image or there is no visible character in the second sub-image if a difference between the second variance and the first variance is smaller than or equal to the second threshold.
it is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 5 is a schematic block diagram of a banknote recognition terminal device according to an embodiment of the present invention. As shown in fig. 5, the banknote recognition terminal device 5 of this embodiment includes: a processor 50, a memory 51 and a computer program 52 stored in said memory 51 and executable on said processor 50. The processor 50, when executing the computer program 52, implements the steps in the above-described respective banknote recognition method embodiments, such as the steps S101 to S108 shown in fig. 1. Alternatively, the processor 50, when executing the computer program 52, implements the functions of each module/unit in the above-mentioned device embodiments, for example, the functions of the modules 401 to 408 shown in fig. 4.
illustratively, the computer program 52 may be partitioned into one or more modules/units that are stored in the memory 51 and executed by the processor 50 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution process of the computer program 52 in the bill recognizing terminal device 5. For example, the computer program 52 may be divided into a prefix number extraction module, an area division module, a first pixel group extraction module, a second pixel group extraction module, a first average gradation value calculation module, a second average gradation value calculation module, a first determination module, and a second determination module.
The banknote recognition terminal 5 may be a terminal such as a banknote validator, a deposit machine, a cash dispenser, and a cash recycling machine. The banknote recognition terminal device may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will appreciate that fig. 5 is merely an example of the banknote recognition terminal 5, and does not constitute a limitation to the banknote recognition terminal 5, and may include more or less components than those shown, or combine some components, or different components, for example, the banknote recognition terminal 5 may further include an input/output device, a network access device, a bus, and the like.
the Processor 50 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
the memory 51 may be an internal storage unit of the banknote recognition terminal 5, such as a hard disk or an internal memory of the banknote recognition terminal 5. The memory 51 may also be an external storage device of the paper money identification terminal device 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the paper money identification terminal device 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the banknote recognition terminal device 5. The memory 51 is used to store the computer program and other programs and data required by the bill identifying terminal device 5. The memory 51 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
in the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
in addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
the integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (14)
1. A banknote recognition method, comprising:
extracting an area where a crown word number of the paper money to be identified is located from a first image, wherein the first image is an image displayed by the paper money to be identified under the irradiation of visible light in a red waveband;
dividing the region where the crown word number of the paper money to be recognized is located into a first sub-region where a first character is located and a second sub-region where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized;
extracting a first pixel group occupied by the first character from the first sub-area;
Extracting a second pixel group occupied by the second character from the second sub-area;
respectively calculating a first average gray value of the first pixel group and a second average gray value of the second pixel group;
if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value, judging that the paper money to be identified is a genuine money, wherein the first threshold value is a positive number;
if the difference value obtained by subtracting the second average gray value from the first average gray value is smaller than or equal to the first threshold value, judging the paper money to be identified as abnormal paper money;
The region where the crown word number of the paper money to be identified is extracted from the first image comprises:
intercepting a possible area of the crown word number on the first image, and performing binarization processing on the intercepted gray level image of the possible area to obtain a binary image of the possible area;
moving a first moving window on the binary image of the possible area line by line, acquiring a pixel accumulated value of an area where the current first moving window is located, and determining that a first line of the area where the first moving window is located is a starting line of the area where the prefix number is located when the pixel accumulated value of the first moving window is the maximum value;
Moving a second moving window row by row, acquiring a pixel accumulated value of an area where the current second moving window is located, and determining that a first row of the area where the second moving window is located is a starting row of the area where the prefix is located when the pixel accumulated value of the second moving window is the maximum value;
and extracting the area where the crown word number of the paper money to be identified is located according to the initial row, the initial column and the height and width of the area where the known crown word number is located.
2. The banknote recognition method according to claim 1, wherein the dividing of the area of the crown word number of the banknote to be recognized into a first sub-area in which a first character is located and a second sub-area in which a second character is located comprises:
acquiring first lengths of areas where the first four characters in the standard serial number are located in the character arrangement direction, wherein the standard serial number is a preset serial number of standard paper money corresponding to the paper money to be recognized;
Acquiring second lengths of areas where the last six characters in the standard crown word size are located in the character arrangement direction;
Calculating a first ratio of the first length to the second length;
And sequentially dividing the region where the crown word number of the paper money to be recognized is located into the first sub-region and the second sub-region in the character arrangement direction, so that a second ratio is equal to the first ratio, wherein the second ratio is the ratio of the length of the first sub-region in the character arrangement direction to the length of the second sub-region in the character arrangement direction.
3. the banknote recognition method of claim 1, wherein said extracting the first pixel group occupied by the first character from the first sub-region comprises:
carrying out binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region;
Extracting the first pixel group from the first sub-area according to the binarization image of the first sub-area;
The extracting of the second pixel group occupied by the second character from the second sub-area includes:
Carrying out binarization processing on the image of the second sub-area to obtain a binarized image of the second sub-area;
And extracting the second pixel group from the second sub-area according to the binarized image of the second sub-area.
4. The banknote recognition method according to claim 3, wherein the binarizing processing of the image of the first sub-area includes:
carrying out binarization processing on the image of the first sub-region by using an adaptive threshold value binarization algorithm;
The binarization processing of the image of the second sub-area comprises:
And carrying out binarization processing on the image of the second sub-area by using an adaptive threshold value binarization algorithm.
5. the banknote recognition method according to any one of claims 1 to 4, further comprising, after determining that the banknote to be recognized is a genuine banknote:
Respectively acquiring a first sub-image presented by the first sub-area under the irradiation of infrared light and a second sub-image presented by the second sub-area under the irradiation of the infrared light;
judging whether visible characters exist in the first sub-image and whether visible characters exist in the second sub-image;
if the visible characters do not exist in the first sub-image and the visible characters exist in the second sub-image, the fact that the paper money to be recognized is true is determined, and the judgment result that the paper money to be recognized is the true money is verified;
and if the visible characters exist in the first sub-image or the second sub-image, determining that the judgment result that the paper money to be recognized is the true money is verified to be false.
6. The banknote recognition method of claim 5, wherein said determining whether visible characters are present in the first sub-image and whether visible characters are present in the second sub-image comprises:
respectively calculating a first variance of the pixel group gray value of the first sub-image and a second variance of the pixel group gray value of the second sub-image;
If the difference value of subtracting the first variance from the second variance is larger than a preset second threshold value, determining that no visible character exists in the first sub-image and no visible character exists in the second sub-image, wherein the second threshold value is a positive number;
and if the difference value of the second variance minus the first variance is less than or equal to the second threshold, determining that visible characters exist in the first sub-image or visible characters do not exist in the second sub-image.
7. a paper money discriminating apparatus characterized by comprising:
the system comprises a crown word number extraction module, a first image processing module and a second image processing module, wherein the crown word number extraction module is used for extracting an area where a crown word number of a paper currency to be identified is located from a first image, and the first image is an image displayed by the paper currency to be identified under the irradiation of visible light in a red wave band; specifically, a possible region of the crown word number on the first image is intercepted, and binarization processing is performed on the intercepted gray level image of the possible region to obtain a binary image of the possible region; moving a first moving window on the binary image of the possible area line by line, acquiring a pixel accumulated value of an area where the current first moving window is located, and determining that a first line of the area where the first moving window is located is a starting line of the area where the prefix number is located when the pixel accumulated value of the first moving window is the maximum value; moving a second moving window row by row, acquiring a pixel accumulated value of an area where the current second moving window is located, and determining that a first row of the area where the second moving window is located is a starting row of the area where the prefix is located when the pixel accumulated value of the second moving window is the maximum value; extracting the area where the crown word number of the paper money to be identified is located according to the initial row, the initial column and the height and width of the area where the known crown word number is located;
The area dividing module is used for dividing the area where the crown word number of the paper money to be recognized is located into a first sub-area where a first character is located and a second sub-area where a second character is located, wherein the first character is the first four characters in the crown word number of the paper money to be recognized, and the second character is the last six characters in the crown word number of the paper money to be recognized;
a first pixel group extraction module, configured to extract a first pixel group occupied by the first character from the first sub-region;
The second pixel group extraction module is used for extracting a second pixel group occupied by the second character from the second sub-area;
the first average gray value calculation module is used for calculating a first average gray value of the first pixel group;
a second average gray value calculation module for calculating a second average gray value of the second pixel group;
the first judging module is used for judging that the paper money to be identified is a genuine money if the difference value obtained by subtracting the second average gray value from the first average gray value is larger than a preset first threshold value, and the first threshold value is a positive number;
and the second judging module is used for judging that the paper money to be identified is abnormal money if the difference value obtained by subtracting the second average gray value from the first average gray value is less than or equal to the first threshold value.
8. The banknote recognition device according to claim 7, wherein the area division module comprises:
The first length obtaining unit is used for obtaining the first length of an area where the first four characters in the standard serial number are located in the character arrangement direction, and the standard serial number is the preset serial number of the standard paper currency corresponding to the paper currency to be identified;
a second length obtaining unit, configured to obtain second lengths of areas where the last six characters in the standard prefix number are located in the character arrangement direction;
a first ratio calculation unit for calculating a first ratio of the first length to the second length;
And the area dividing unit is used for sequentially dividing the area where the crown word number of the paper money to be recognized is located into the first sub-area and the second sub-area in the character arrangement direction, so that a second ratio is equal to a first ratio, and the second ratio is the ratio of the length of the first sub-area in the character arrangement direction to the length of the second sub-area in the character arrangement direction.
9. The banknote recognition apparatus according to claim 7, wherein the first pixel group extraction module comprises:
The first processing unit is used for carrying out binarization processing on the image of the first sub-region to obtain a binarized image of the first sub-region;
A first extraction unit configured to extract the first pixel group from the first sub-region based on a binarized image of the first sub-region;
the second pixel group extraction module includes:
the second processing unit is used for carrying out binarization processing on the image of the second sub-area to obtain a binarized image of the second sub-area;
a second extraction unit configured to extract the second pixel group from the second sub-region based on the binarized image of the second sub-region.
10. The banknote recognition apparatus according to claim 9, wherein the first processing unit includes:
The first processing subunit is used for carrying out binarization processing on the image of the first sub-region by using an adaptive threshold value binarization algorithm;
The second processing unit includes:
And the second processing subunit is used for performing binarization processing on the image of the second sub-region by using an adaptive threshold value binarization algorithm.
11. the banknote recognition apparatus according to any one of claims 7 to 10, further comprising:
the first sub-image acquisition module is used for acquiring a first sub-image presented by the first sub-area under the irradiation of infrared light;
The second sub-image acquisition module is used for acquiring a second sub-image presented by the second sub-area under the irradiation of the infrared light;
The visible character judgment module is used for judging whether visible characters exist in the first sub-image and whether visible characters exist in the second sub-image;
the first checking module is used for determining that the judgment result that the paper money to be identified is the true paper money is checked to be true if the visible characters do not exist in the first sub-image and the visible characters exist in the second sub-image;
And the second checking module is used for determining that the judgment result that the paper money to be recognized is the true money is checked to be false if the visible characters exist in the first sub-image or the visible characters do not exist in the second sub-image.
12. The banknote recognition device according to claim 11, wherein the visible character determination module includes:
a first variance calculating unit for calculating a first variance of the pixel group gradation values of the first sub-image;
a second variance calculating unit for calculating a second variance of the pixel group gradation value of the second sub-image;
A first determining unit, configured to determine that there is no visible character in the first sub-image and there is a visible character in the second sub-image if a difference between the second variance and the first variance is greater than a preset second threshold, where the second threshold is a positive number;
a second determining unit, configured to determine that there is a visible character in the first sub-image or no visible character in the second sub-image if a difference between the second variance and the first variance is smaller than or equal to the second threshold.
13. a banknote recognition terminal device comprising a memory, a processor and a computer program stored in said memory and executable on said processor, characterized in that said processor implements the steps of the banknote recognition method according to any one of claims 1 to 6 when executing said computer program.
14. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of a banknote recognition method according to any one of claims 1 to 6.
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| CN110473333A (en) * | 2019-07-11 | 2019-11-19 | 深圳怡化电脑股份有限公司 | Detection method, detection device and the terminal of note number |
| CN112308056A (en) * | 2019-07-26 | 2021-02-02 | 深圳怡化电脑股份有限公司 | Method, device and equipment for acquiring note characteristic region and storage medium |
| CN110867015A (en) * | 2019-09-29 | 2020-03-06 | 广州国瀚计算机通讯科技有限公司 | RMB counterfeit discriminating method |
| CN111340900A (en) * | 2020-02-18 | 2020-06-26 | 上海理工大学 | Image compression method based on double complex wavelets |
| CN111723663B (en) * | 2020-05-18 | 2024-01-23 | 中国农业科学院农业环境与可持续发展研究所 | Mulch film identification method, device and storage medium |
| CN112232331A (en) * | 2020-12-17 | 2021-01-15 | 恒银金融科技股份有限公司 | Recognition and classification method for infrared image characteristic region of paper money |
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| CN101908241A (en) * | 2010-08-03 | 2010-12-08 | 广州广电运通金融电子股份有限公司 | Method and system for identifying valued documents |
| CN102890840A (en) * | 2012-08-22 | 2013-01-23 | 山东新北洋信息技术股份有限公司 | Method and device for identifying paper money |
| CN103136845A (en) * | 2013-01-23 | 2013-06-05 | 浙江大学 | Renminbi (RMB) counterfeit identifying method based on crown-word image characters |
| CN104063939A (en) * | 2014-06-20 | 2014-09-24 | 威海华菱光电股份有限公司 | Target object authenticity verifying method and device |
| CN106780957A (en) * | 2016-11-18 | 2017-05-31 | 光荣电子工业（苏州）有限公司 | Image acquiring device, paper products processing unit and image acquiring method |
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