CN116758530A - Anti-cheating truck weighing system - Google Patents
Anti-cheating truck weighing system Download PDFInfo
- Publication number
- CN116758530A CN116758530A CN202310667520.7A CN202310667520A CN116758530A CN 116758530 A CN116758530 A CN 116758530A CN 202310667520 A CN202310667520 A CN 202310667520A CN 116758530 A CN116758530 A CN 116758530A
- Authority
- CN
- China
- Prior art keywords
- license plate
- truck
- weighing
- image
- plate number
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000005303 weighing Methods 0.000 title claims abstract description 109
- 238000000034 method Methods 0.000 claims abstract description 35
- 238000001514 detection method Methods 0.000 claims description 13
- 238000012544 monitoring process Methods 0.000 claims description 6
- 230000000875 corresponding effect Effects 0.000 description 12
- 230000000694 effects Effects 0.000 description 9
- 238000004364 calculation method Methods 0.000 description 8
- 239000003086 colorant Substances 0.000 description 8
- 238000010586 diagram Methods 0.000 description 3
- 230000006399 behavior Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 2
- 239000002131 composite material Substances 0.000 description 2
- 230000002596 correlated effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000003313 weakening effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
-
- 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
- G06V10/56—Extraction of image or video features relating to colour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/625—License plates
Abstract
The application belongs to the field of image recognition, and discloses a truck weighing system capable of preventing cheating, which comprises a license plate shooting module, a license plate recognition module and a license plate comparison module; the license plate shooting module is used for shooting a truck entering the loading area to obtain a first image containing a license plate, and shooting a truck leaving the loading area to obtain a second image containing the license plate; the license plate recognition module is used for recognizing the first image and the second image based on the improved image graying algorithm to obtain a first license plate number and a second license plate number; the license plate comparison module is used for judging whether the vehicles in and out are consistent according to the first license plate number and the second license plate number, and obtaining a judgment result. The application effectively improves the information content of the license plate region in the image after graying, further improves the accuracy of the identified license plate number and improves the efficiency of preventing the behavior of weighing cheating in the weighing process.
Description
Technical Field
The application relates to the field of image recognition, in particular to a truck weighing system capable of preventing cheating.
Background
In the existing truck weighing system, for example, patent with publication number of CN112129391A, in order to prevent cheating of trucks, for example, inconsistent in-and-out vehicles, license plates of the trucks are generally identified during weighing, then the measured weight is matched with the license plates, the in-and-out trucks are ensured to be identical, and the measured weight is stored after the license plate numbers are identified to be consistent.
However, in the existing license plate recognition algorithm, for example, in the patent with publication number CN114495082a, in the process of graying, the gray image is generally obtained by performing weighted summation processing on three component images in the RGB color model, and because the weights of the three component images are preset, the weights are kept unchanged when the license plates with different base colors are grayed, and therefore, compared with the original image, the obtained gray image has a larger information content reduction range in the license plate region, which is unfavorable for accurately recognizing the license plate of the truck, thereby preventing the truck from cheating in the weighing process.
Disclosure of Invention
The application aims to disclose a weight-calculating system of a truck for preventing cheating, which solves the problem that a license plate region in an image obtained after graying has higher information content in the process of identifying a license plate of the truck when the truck is prevented from cheating in the weight-calculating process.
In order to achieve the above purpose, the present application provides the following technical solutions:
a weight-counting system of a truck for preventing cheating comprises a license plate shooting module, a license plate recognition module and a license plate comparison module;
the license plate shooting module is used for shooting a truck entering the loading area to obtain a first image containing a license plate, and shooting a truck leaving the loading area to obtain a second image containing the license plate;
the license plate recognition module is used for recognizing the first image and the second image to obtain a first license plate number and a second license plate number;
the license plate comparison module is used for judging whether the vehicles in and out are consistent according to the first license plate number and the second license plate number, and obtaining a judgment result;
the method for identifying the first image and the second image to obtain a first license plate number and a second license plate number comprises the following steps:
s1, carrying out graying processing on a first image and a second image by adopting an improved image graying algorithm to obtain a first gray image and a second gray image:
for the image delpho, delpho epsilon { first image, second image }, the process of graying the delpho using the improved graying algorithm to obtain the gray image corresponding to delpho includes:
acquiring a set of preset gray weight combinations;
carrying out graying treatment on delpho by using each gray weight combination in the gray weight set respectively to obtain a plurality of intermediate images;
calculating the effective information coefficient of each intermediate image respectively, and taking the intermediate image with the maximum effective information coefficient as a gray level image corresponding to delpho;
s2, respectively carrying out image recognition on the first gray level image and the second gray level image to obtain a first license plate number and a second license plate number.
Preferably, the truck further comprises a weighing module, wherein the weighing module is used for weighing a truck with a license plate number of a first license plate number entering the loading area to obtain a first weight, and is used for weighing a truck with a license plate number of a second license plate number leaving the loading area to obtain a second weight.
Preferably, the vehicle loading and unloading system further comprises a storage module, wherein the storage module is used for subtracting the first weight from the second weight when the judgment result is that the vehicles in and out are consistent, obtaining the weight of the goods on the truck, and storing the weight of the goods and the first license plate number after being correlated.
Preferably, the license plate recognition module is further configured to store the first license plate number, and obtain a first license plate number set.
Preferably, determining whether the first license plate number is consistent with the second license plate number, to obtain a determination result, includes:
and comparing the second license plate number with each element in the first license plate number set, and if the elements which are the same as the second license plate number exist in the first license plate number set, judging that the vehicles in and out are consistent.
Preferably, the system further comprises a monitoring module, wherein the monitoring module is used for shooting the weighing process of the truck and obtaining a video of the weighing process;
the storage module is used for storing video of the weighing process.
Preferably, the weighing module comprises a detection unit and a weighing unit;
the detection unit is used for detecting whether the truck completely enters the weighing area;
the weighing unit is used for weighing the truck with the license plate number of the loading area being the first license plate number after the truck completely enters the weighing area, so as to obtain the first weight, and is used for weighing the truck with the license plate number of the loading area being the second license plate number, so as to obtain the second weight.
Preferably, the weighing zone comprises a first boundary and a second boundary perpendicular to the direction of advance of the truck and a third boundary and a fourth boundary parallel to the direction of advance of the truck, the first boundary, the second boundary, the third boundary and the fourth boundary forming a rectangular zone.
Preferably, the detection unit comprises a first infrared correlation device, a second infrared correlation device and a judgment device;
the first infrared correlation device and the second infrared correlation device are respectively arranged at the positions of a first boundary and a second boundary of the weighing area, which are perpendicular to the advancing direction of the truck;
the first infrared correlation device and the second infrared correlation device are respectively used for judging whether a first boundary and a second boundary have shielding objects or not, and a first shielding result and a second shielding result are obtained;
the weighing unit is also used for acquiring the real-time weight of the weighing area;
the judging device is used for detecting whether the truck completely enters the weighing area according to the first shielding result, the second shielding result and the real-time weight.
Preferably, detecting whether the truck completely enters the weighing area according to the first shielding result, the second shielding result and the real-time weight comprises the following steps:
judging whether the real-time weight is larger than a preset weight threshold, if so, performing the next step of judgment, and if not, indicating that the truck does not enter a weighing area;
the next step of judgment comprises the following steps:
and if the first shielding result is that the shielding object exists and/or the second shielding result is that the shielding object exists, the fact that the truck does not completely enter the weighing area is indicated.
When the application prevents the cheating of the truck in the weighing process, the improved image graying algorithm is adopted to carry out graying treatment on the image containing the license plate number, so that the information content of the license plate region in the image after graying is effectively improved, the accuracy of the identified license plate number is further improved, the repeated identification of the license plate number is avoided, the waiting time of the truck passing through the weighing region is shortened, and the efficiency of preventing the action of weighing cheating in the weighing process is effectively improved.
The improved image graying algorithm is characterized in that different gray weight combinations are set for license plates with different base colors in advance, the gray weight combinations are used for graying images containing license plate numbers, and then an image with the largest effective information is selected from a plurality of obtained intermediate images to serve as a final gray image, so that the information content of license plate areas in the gray image is improved.
Drawings
The present disclosure will become more fully understood from the detailed description given herein below and the accompanying drawings, which are given by way of illustration only, and thus are not limiting of the present disclosure, and wherein:
FIG. 1 is a schematic diagram of a tamper resistant truck weighing system according to the present application.
FIG. 2 is a second schematic diagram of a tamper-resistant truck weighing system of the present application.
FIG. 3 is a third schematic diagram of a tamper resistant truck weighing system of the present application.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
The application provides a weight system of a truck for preventing cheating, which is shown in an embodiment in fig. 1, and comprises a license plate shooting module, a license plate recognition module and a license plate comparison module;
the license plate shooting module is used for shooting a truck entering the loading area to obtain a first image containing a license plate, and shooting a truck leaving the loading area to obtain a second image containing the license plate;
the license plate recognition module is used for recognizing the first image and the second image to obtain a first license plate number and a second license plate number;
the license plate comparison module is used for judging whether the vehicles in and out are consistent according to the first license plate number and the second license plate number, and obtaining a judgment result;
the method for identifying the first image and the second image to obtain a first license plate number and a second license plate number comprises the following steps:
s1, carrying out graying processing on a first image and a second image by adopting an improved image graying algorithm to obtain a first gray image and a second gray image:
for the image delpho, delpho epsilon { first image, second image }, the process of graying the delpho using the improved graying algorithm to obtain the gray image corresponding to delpho includes:
acquiring a set of preset gray weight combinations;
carrying out graying treatment on delpho by using each gray weight combination in the gray weight set respectively to obtain a plurality of intermediate images;
calculating the effective information coefficient of each intermediate image respectively, and taking the intermediate image with the maximum effective information coefficient as a gray level image corresponding to delpho;
s2, respectively carrying out image recognition on the first gray level image and the second gray level image to obtain a first license plate number and a second license plate number.
When the application prevents the cheating of the truck in the weighing process, the improved image graying algorithm is adopted to carry out graying treatment on the image containing the license plate number, so that the information content of the license plate region in the image after graying is effectively improved, the accuracy of the identified license plate number is further improved, the repeated identification of the license plate number is avoided, the waiting time of the truck passing through the weighing region is shortened, and the efficiency of preventing the action of weighing cheating in the weighing process is effectively improved.
The improved image graying algorithm is characterized in that different gray weight combinations are set for license plates with different base colors in advance, the gray weight combinations are used for graying images containing license plate numbers, and then an image with the largest effective information is selected from a plurality of obtained intermediate images to serve as a final gray image, so that the information content of license plate areas in the gray image is improved.
Preferably, the gray weight combination includes weights of three components of red, green, and blue in the RGB color model during the graying process.
Preferably, the set of gray weight combinations includes gray weight combinations corresponding to license plates with different ground colors.
Preferably, the gray weight combination of license plates with different base colors is obtained by the following method:
for license plates with the base color of Q, obtaining the values Q of three components of red, green and blue in an RGB color model R 、Q G 、Q B ；
Calculating deviation values dvival (Q) of three components of color, green and blue R )、dvival(Q G )、dvival(Q B )：
dvival(Q R )＝255-Q R
dvival(Q G )＝255-Q G
dvival(Q B )＝255-Q B
The component with the smallest deviation value is used as a component S needing weight adjustment;
the weights of the components S after adjustment are:
w S,af ＝w S -δ S
wherein w is S,af And w S Respectively represent the weights after and before the adjustment of the component S, delta S The adjustment amount of the component S is indicated,
the other two components except S are denoted by T and U respectively,
the adjusted weights for component T are:
the adjusted weights for component U are:
wherein w is T,af And w T Respectively representing the weights of the component T after and before adjustment, V represents the adjustment amplitude control coefficient, and V is larger than or equal to 3,w U,af And w U Respectively representing the weights of the component U after adjustment and before adjustment;
the gray weight combination corresponding to the license plate with the base color Q is { w } S,af ,w T,af ,w U,af }。
According to the application, the gray weight combination obtaining process can carry out self-adaptive obtaining according to the specific color value of the base color of the license plate, so that the manual workload is effectively reduced, the gray weight combination obtaining efficiency is effectively improved, and the implementation difficulty of the application is reduced.
Specifically, in the process of acquiring weights of three different components of red, green and blue, the weight of the component with the smallest deviation value is reduced, and the weights of the other two components are increased, so that the difference between the pixel points of the area where the license plate number is positioned and the pixel points of the license plate base color area is improved, the effect of highlighting the pixel points of the license plate number is achieved, and the information content of the license plate area in the gray image is improved.
Preferably, if there are more than two components whose deviation values agree, the component S to be weight-adjusted is determined as follows:
obtaining the numerical value L of three components of red, green and blue in an RGB color model of the color of a license plate number in a license plate with the base color Q R 、L G 、L B ，
Calculate L R And Q is equal to R Absolute value dif of difference of (2) R Calculate L G And Q is equal to G Absolute value dif of difference of (2) G Calculate L B And Q is equal to B Absolute value dif of difference of (2) B ，
The component corresponding to the largest absolute value among the three absolute values is taken as a component S.
Specifically, for some special ground colors, such as standard gray, the calculated deviation values are the same, and at this time, the difference between the color of the license plate number and the color of the license plate in the RGB color model is further calculated to obtain the component S, so that the component with better highlighting effect on the license plate number after adjustment can be effectively obtained.
The following are further examples:
the weights of the corresponding images in the RGB color model for the red, green and blue components in the prior art are 0.299, 0.587 and 0.114,
for license plates with blue base colors, the corresponding gray weight combination is expressed as { w } R,blue ,w G,blue ,w B,blue }，w R,blue 、w G,blue 、w B,blue The image of the license plate respectively representing blue is weighted on the corresponding image by the three components of red, green and blue in the RGB color model,
then w R,blue The calculation function of (2) is:
delta represents the adjustment quantity, delta belongs to (0.05,0.114);
w G,blue the calculation function of (2) is:
w B,blue the calculation function of (2) is:
w B,blue ＝0.114-δ。
in the above embodiment, the weight of the blue component is reduced, so that the difference between the gray value of the font on the license plate and the gray value of the surrounding pixel point is larger in the image after graying, thereby achieving the effect of highlighting the license plate number and improving the information content of the license plate region in the gray image.
In other embodiments, for the base color other than blue, the effect of highlighting the license plate number in the image is achieved by weakening the weight of the color closest to the base color. The base color of the license plate is decomposed to obtain three colors of red, green and blue, and the color with the largest numerical value is the color closest to the base color.
Preferably, for the intermediate image midho, the effective information coefficient is calculated in the following manner:
first, acquiring a set reppix of representative pixel points in an intermediate image midho:
calculating the area value of each pixel point in the intermediate image midho respectively, taking the pixel point with the area value larger than the set area value threshold value as the element of reppix,
the calculation function of the area value is:
wherein bkval h Region value λ representing pixel point h 1 、λ 2 、λ 3 Representing three preset weights, neimx h And neimi h Each of which represents a square region squ centered on the pixel H and having a side length of H h Maximum and minimum gray values of the pixel points in the pixel array, H is an odd number, and gray is a gray h Gradation value, cprval, representing pixel h h A composite value indicating the pixel h, stdcpr indicating the set maximum value of the composite value;
the calculation function of the integrated value is:
cprval h ＝|max(num sml,h,lf ,num bgr,h,lf )-max(num sml,h,rg ,num bgr,h,rg )|
wherein max represents the larger value in brackets, num sml,h,lf Representing the abscissa smaller than the pixel h and at squ h The number of pixels having gray values smaller than the pixel h, num bgr,h,lf The abscissa is smaller than the pixel h and is squ h The number of pixels having a gray value larger than the pixel h, num sml,h,rg Representing an abscissa larger than the pixel h and at squ h The number of pixels having gray values smaller than the pixel h, num bgr,h,rg Representing an abscissa larger than the pixel h and at squ h The number of pixels having a gray value greater than the pixel h;
second, calculating the effective information coefficient based on the set reppix of the representative pixel points:
the calculation function of the effective information coefficient is as follows:
wherein, efinaf represents the effective information coefficient, μ represents the summation ratio, μ∈ (0.1,0.9), grayfs represents the preset variance constant, nreppix represents the total number of pixel points in reppix, and gray z Representation ofGray value of pixel point z, mnei z Represents a square region squ centered on the pixel point z and having a side length G z In the number of elements belonging to the set reppix, G is an odd number.
The calculation process of the effective information coefficient is closely related to the salient effect of the gray weight combination, and the better the salient effect is, the larger the numerical value of the effective information coefficient is, so that the intermediate image with the best salient effect can be selected through the effective information coefficient. The method is beneficial to improving the accuracy of license plate recognition, thereby improving the efficiency of preventing the heavy cheating behavior.
The application selects the representative pixel point through the area value, wherein the representative pixel point is a pixel point with large minimum difference with the gray values of surrounding pixel points, but small maximum difference with the gray values of surrounding pixel points and small comprehensive value. The probability of a pixel belonging to the portion of the edge of the license plate number is relatively large. Square region squ corresponding to pixel h h The larger the difference between the maximum value and the minimum value of the gray value, the smaller the difference between the pixel point h and the maximum value of the gray value, and the smaller the integrated value, the larger the area value. The effective information coefficient is calculated based on the pixel points, so that the effective information coefficient fully represents the difference between the pixel points of the license plate number area and the pixel points of the ground color area, and the middle image with the largest difference in the middle images, namely the middle image with the best highlighting effect, is selected to be used as the image for image recognition.
The integrated value is compared with the difference value between the number of the pixel points belonging to the font area and the number of the pixel points not belonging to the font area in the areas at two sides of the pixel points, and the smaller the difference value is, the larger the probability that the pixel point h is positioned at the edge of the font area of the license plate number is.
The effective information coefficient is mainly calculated from two aspects of the distribution range and the continuity of the gray values of the pixels in the reppix, and the smaller the distribution range is, the better the continuity is, the larger the effective information coefficient is, so that an intermediate image with large proportion and good continuity of the pixels containing the license plate region in the reppix can be selected. The method is favorable for selecting the intermediate image with the best highlighting effect. Because the previous screening process of the representative pixel points may be interfered by the noise pixel points in the selection process, so that part of the noise pixel points are erroneously selected as the representative pixel points, obviously, the number of the noise pixel points in the reppix is higher, and the accurate effective information coefficient is not beneficial to calculating to represent the effective information condition in the intermediate image, so that the probability that the intermediate image is selected for image recognition can be reduced through continuity detection and distribution range detection, and the accuracy of license plate image recognition is improved.
Preferably, as shown in fig. 2, the system further comprises a weighing module, wherein the weighing module is used for weighing a truck with a license plate number of a first license plate number entering the loading area to obtain a first weight, and is used for weighing a truck with a license plate number of a second license plate number leaving the loading area to obtain a second weight.
Specifically, the license plate shooting module can be arranged outside the weighing area, so that the license plate number of the truck is obtained before weighing.
Preferably, as shown in fig. 3, the vehicle loading and unloading system further comprises a storage module, wherein the storage module is used for subtracting the first weight from the second weight to obtain the weight of the goods on the truck when the judgment result shows that the vehicles loading and unloading are consistent, and storing the weight of the goods and the first license plate number after the weight of the goods is associated.
Specifically, the in-out vehicle consistency judgment can facilitate calculation of the weight of the goods loaded by the delivery vehicle.
Preferably, the license plate recognition module is further configured to store the first license plate number, and obtain a first license plate number set.
Specifically, the license plate recognition module is configured to send the recognized first license plate numbers to the storage module for storage.
Preferably, determining whether the first license plate number is consistent with the second license plate number, to obtain a determination result, includes:
and comparing the second license plate number with each element in the first license plate number set, and if the elements which are the same as the second license plate number exist in the first license plate number set, judging that the vehicles in and out are consistent.
Preferably, the system further comprises a monitoring module, wherein the monitoring module is used for shooting the weighing process of the truck and obtaining a video of the weighing process;
the storage module is used for storing video of the weighing process.
Specifically, the weighing area and the area around the weighing area can be monitored, and the obtained video is stored, so that when a problem occurs later, whether cheating behaviors occur in the weighing process can be effectively judged. For example, some trucks use a skip to enter the weighing area to reduce their own weight, so that when the owner checks the weight, he finds that the weight is not correct, he can detect whether the weighing cheating action is present by video recording.
Preferably, the weighing module comprises a detection unit and a weighing unit;
the detection unit is used for detecting whether the truck completely enters the weighing area;
the weighing unit is used for weighing the truck with the license plate number of the loading area being the first license plate number after the truck completely enters the weighing area, so as to obtain the first weight, and is used for weighing the truck with the license plate number of the loading area being the second license plate number, so as to obtain the second weight.
Specifically, when the truck does not fully perform the weighing area, the weight on the weighing area is much worse than the actual weight of the truck at the moment because the wheels do not fully enter the weighing area, so that in order to improve the accuracy of weighing, the application performs corresponding detection through the detection unit.
Preferably, the weighing zone comprises a first boundary and a second boundary perpendicular to the direction of advance of the truck and a third boundary and a fourth boundary parallel to the direction of advance of the truck, the first boundary, the second boundary, the third boundary and the fourth boundary forming a rectangular zone.
In particular, the weighing area may be an area where the load bearing portion of the wagon balance is located.
Preferably, the detection unit comprises a first infrared correlation device, a second infrared correlation device and a judgment device;
the first infrared correlation device and the second infrared correlation device are respectively arranged at the positions of a first boundary and a second boundary of the weighing area, which are perpendicular to the advancing direction of the truck;
the first infrared correlation device and the second infrared correlation device are respectively used for judging whether a first boundary and a second boundary have shielding objects or not, and a first shielding result and a second shielding result are obtained;
the weighing unit is also used for acquiring the real-time weight of the weighing area;
the judging device is used for detecting whether the truck completely enters the weighing area according to the first shielding result, the second shielding result and the real-time weight.
Specifically, the infrared correlation device comprises a transmitter and a receiver, when the receiver is not shielded, the receiver can normally receive infrared rays, and when the receiver is shielded, the receiver can not receive infrared rays.
Preferably, detecting whether the truck completely enters the weighing area according to the first shielding result, the second shielding result and the real-time weight comprises the following steps:
judging whether the real-time weight is larger than a preset weight threshold, if so, performing the next step of judgment, and if not, indicating that the truck does not enter a weighing area;
the next step of judgment comprises the following steps:
and if the first shielding result is that the shielding object exists and/or the second shielding result is that the shielding object exists, the fact that the truck does not completely enter the weighing area is indicated.
Specifically, the weight threshold is set to avoid starting the weighing process when a non-truck enters the weighing area.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The anti-cheating truck weighing system is characterized by comprising a license plate shooting module, a license plate recognition module and a license plate comparison module;
the license plate shooting module is used for shooting a truck entering the loading area to obtain a first image containing a license plate, and shooting a truck leaving the loading area to obtain a second image containing the license plate;
the license plate recognition module is used for recognizing the first image and the second image to obtain a first license plate number and a second license plate number;
the license plate comparison module is used for judging whether the vehicles in and out are consistent according to the first license plate number and the second license plate number, and obtaining a judgment result;
the method for identifying the first image and the second image to obtain a first license plate number and a second license plate number comprises the following steps:
s1, carrying out graying processing on a first image and a second image by adopting an improved image graying algorithm to obtain a first gray image and a second gray image:
for the image delpho, delpho epsilon { first image, second image }, the process of graying the delpho using the improved graying algorithm to obtain the gray image corresponding to delpho includes:
acquiring a set of preset gray weight combinations;
carrying out graying treatment on delpho by using each gray weight combination in the gray weight set respectively to obtain a plurality of intermediate images;
calculating the effective information coefficient of each intermediate image respectively, and taking the intermediate image with the maximum effective information coefficient as a gray level image corresponding to delpho;
s2, respectively carrying out image recognition on the first gray level image and the second gray level image to obtain a first license plate number and a second license plate number.
2. The anti-cheating truck weighing system of claim 1, further comprising a weighing module for weighing a truck having a first license number entering the loading area to obtain a first weight, and for weighing a truck having a second license number exiting the loading area to obtain a second weight.
3. The anti-cheating truck weighing system of claim 2 further comprising a storage module for subtracting the first weight from the second weight to obtain the weight of the cargo on the truck and storing the weight of the cargo and the first license plate number after correlating the weight of the cargo and the first license plate number when the judgment result indicates that the vehicles are in and out agreement.
4. The anti-cheating truck weighing system of claim 1 wherein the license plate recognition module is further configured to store the first license plate number to obtain the first set of license plate numbers.
5. The anti-cheating truck weighing system of claim 4 wherein determining whether the first license plate number and the second license plate number are identical to one another to obtain a determination result comprises:
and comparing the second license plate number with each element in the first license plate number set, and if the elements which are the same as the second license plate number exist in the first license plate number set, judging that the vehicles in and out are consistent.
6. The anti-cheating truck weighing system of claim 3, further comprising a monitoring module, wherein the monitoring module is used for shooting a weighing process of the truck and obtaining a video of the weighing process;
the storage module is used for storing video of the weighing process.
7. The anti-cheating truck weighing system of claim 2, wherein the weighing module comprises a detection unit and a weighing unit;
the detection unit is used for detecting whether the truck completely enters the weighing area;
the weighing unit is used for weighing the truck with the license plate number of the loading area being the first license plate number after the truck completely enters the weighing area, so as to obtain the first weight, and is used for weighing the truck with the license plate number of the loading area being the second license plate number, so as to obtain the second weight.
8. A tamper-resistant truck weighing system according to claim 7 wherein the weighing area includes first and second boundaries perpendicular to the forward direction of the truck and third and fourth boundaries parallel to the forward direction of the truck, the first, second, third and fourth boundaries comprising a rectangular area.
9. The anti-cheating truck weighing system of claim 8 wherein the detection unit comprises a first infrared correlation device, a second infrared correlation device, and a judgment device;
the first infrared correlation device and the second infrared correlation device are respectively arranged at the positions of a first boundary and a second boundary of the weighing area, which are perpendicular to the advancing direction of the truck;
the first infrared correlation device and the second infrared correlation device are respectively used for judging whether a first boundary and a second boundary have shielding objects or not, and a first shielding result and a second shielding result are obtained;
the weighing unit is also used for acquiring the real-time weight of the weighing area;
the judging device is used for detecting whether the truck completely enters the weighing area according to the first shielding result, the second shielding result and the real-time weight.
10. The anti-cheating truck weighing system of claim 9, wherein detecting whether the truck is fully within the weighing area based on the first occlusion result, the second occlusion result, and the real-time weight comprises:
judging whether the real-time weight is larger than a preset weight threshold, if so, performing the next step of judgment, and if not, indicating that the truck does not enter a weighing area;
the next step of judgment comprises the following steps:
and if the first shielding result is that the shielding object exists and/or the second shielding result is that the shielding object exists, the fact that the truck does not completely enter the weighing area is indicated.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310667520.7A CN116758530A (en) | 2023-06-07 | 2023-06-07 | Anti-cheating truck weighing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310667520.7A CN116758530A (en) | 2023-06-07 | 2023-06-07 | Anti-cheating truck weighing system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116758530A true CN116758530A (en) | 2023-09-15 |
Family
ID=87954459
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310667520.7A Pending CN116758530A (en) | 2023-06-07 | 2023-06-07 | Anti-cheating truck weighing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116758530A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104200431A (en) * | 2014-08-21 | 2014-12-10 | 浙江宇视科技有限公司 | Processing method and processing device of image graying |
| WO2016145880A1 (en) * | 2015-09-30 | 2016-09-22 | 中兴通讯股份有限公司 | Terminal positioning method and device |
| CN112129391A (en) * | 2020-09-14 | 2020-12-25 | 广东科达计量科技有限公司 | Anti-cheating unattended weighing system |
| CN214010505U (en) * | 2020-12-11 | 2021-08-20 | 中物智建(武汉)科技有限公司 | Unattended intelligent wagon balance capable of improving license plate recognition rate |
| CN113674466A (en) * | 2021-08-09 | 2021-11-19 | 中国水利水电第八工程局有限公司 | Unattended weighbridge weighing system and control method thereof |
| CN114154928A (en) * | 2021-11-29 | 2022-03-08 | 重庆允成互联网科技有限公司 | Anti-cheating truck weighing system |
| CN217483657U (en) * | 2022-03-24 | 2022-09-23 | 重庆千变科技有限公司 | Wagon balance anti-cheating system |
-
2023
- 2023-06-07 CN CN202310667520.7A patent/CN116758530A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104200431A (en) * | 2014-08-21 | 2014-12-10 | 浙江宇视科技有限公司 | Processing method and processing device of image graying |
| WO2016145880A1 (en) * | 2015-09-30 | 2016-09-22 | 中兴通讯股份有限公司 | Terminal positioning method and device |
| CN112129391A (en) * | 2020-09-14 | 2020-12-25 | 广东科达计量科技有限公司 | Anti-cheating unattended weighing system |
| CN214010505U (en) * | 2020-12-11 | 2021-08-20 | 中物智建(武汉)科技有限公司 | Unattended intelligent wagon balance capable of improving license plate recognition rate |
| CN113674466A (en) * | 2021-08-09 | 2021-11-19 | 中国水利水电第八工程局有限公司 | Unattended weighbridge weighing system and control method thereof |
| CN114154928A (en) * | 2021-11-29 | 2022-03-08 | 重庆允成互联网科技有限公司 | Anti-cheating truck weighing system |
| CN217483657U (en) * | 2022-03-24 | 2022-09-23 | 重庆千变科技有限公司 | Wagon balance anti-cheating system |
Non-Patent Citations (2)
| Title |
|---|
| ALI GUNES 等: "Optimizing the color-to-grayscale conversion for image classification", IMAGE AND VIDEO PROCESSING * |
| 钟彩 等: "一种车牌图像的预处理方法", 电脑编程技巧与维护, no. 11 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8103105B2 (en) | Object detection device, and object detection device for elevator | |
| US8189913B2 (en) | Method for detecting shadow of object | |
| EP1814080A1 (en) | Method and apparatus for adjusting the contrast of an image | |
| US5243663A (en) | Vehicle detecting method and apparatus performing binary-conversion processing and luminance variation processing | |
| JP6571424B2 (en) | Fault diagnosis device | |
| CN106161974B (en) | Utilize the display apparatus and its method of high dynamic range function | |
| EP2068569A1 (en) | Method of and apparatus for detecting and adjusting colour values of skin tone pixels | |
| US8619162B2 (en) | Image processing apparatus and method, and image processing program | |
| CN111275658A (en) | Camera shielding detection method and system | |
| CN112991348A (en) | Vehicle chassis foreign matter detection method and device and storage medium | |
| CN116758530A (en) | Anti-cheating truck weighing system | |
| CN113344907B (en) | Image detection method and device | |
| CN114240985B (en) | Method, device, equipment, medium and product for determining grain reserves | |
| CN116843887A (en) | Vehicle-mounted cargo mobile identification system, method, equipment and storage medium | |
| CN116342440A (en) | Vehicle-mounted video monitoring management system based on artificial intelligence | |
| JP4861922B2 (en) | Car color judgment device | |
| CN113989285B (en) | Belt deviation monitoring method, device and equipment based on image and storage medium | |
| US8675971B2 (en) | Method and apparatus for classifying image pixels | |
| EP1744565B1 (en) | Method and apparatus for analysing image data | |
| CN115880181A (en) | Method, device and terminal for enhancing image contrast | |
| CN113901941A (en) | Cargo vehicle checking method and device, electronic device and storage medium | |
| EP1919189B1 (en) | Method and apparatus for processing digital images | |
| CN112804520A (en) | High-speed monitoring video quality detection method | |
| CN115601606B (en) | Store state detection method, device, equipment and storage medium | |
| CN115909254B (en) | DMS system based on camera original image and image processing method thereof |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |