A comparative authentication method and operation management system based on image measurement

Abstract

The present application relates to a comparative authentication method and operation management system based on image measurement, the method comprising: in response to a received task order, obtaining a first key object image of a storage area pointed to by storage information in the task order; continuing to obtain a first person object image obtained at the storage area, binding the first key object image and the first person object image; sending a task order to a terminal to which the first person object image belongs; obtaining a second key object image and a second person object image at the storage area; comparing the first key object image and the second key object image; comparing the first person object image and the second person object image; when the first comparison result and the second comparison result are both consistent, closing the storage area. The comparative authentication method and operation management system based on image measurement disclosed in the present application confirms vehicle keys and staff members through structured light to ensure the consistency of vehicle keys and staff members.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a comparative authentication method and operation management system based on image measurement. Background Art

[0002] At present, car washing services are mainly divided into fixed-location car washing (car wash shops, car wash factories, self-service car wash shops) and non-fixed-location car washing (door-to-door car washing). As the requirements for car washing water in cities become increasingly stringent, non-fixed-location car washing has begun to be accepted. There are two types of non-fixed-location car washing technologies: waterless car washing and micro-water car washing, mainly because these two technologies have advantages in equipment size, water consumption and operability.

[0003] A newer management method is to select an area as the car wash area, such as a parking lot, which can achieve a certain degree of customer concentration and reduce travel time costs. At the same time, the owner's keys are stored in an unmanned box to facilitate the movement of the vehicle, but this method has the potential risk of people and keys being replaced by photos. Summary of the invention

[0004] The present application provides a comparative authentication method and operation management system based on image measurement, which uses structured light to confirm vehicle keys and staff to ensure the consistency of vehicle keys and staff.

[0005] The above-mentioned purpose of the present application is achieved through the following technical solutions:

[0006] In a first aspect, the present application provides a comparative authentication method based on image measurement, comprising:

[0007] In response to the received task order, acquiring a first key object image of a storage area pointed to by storage information in the task order;

[0008] Continue to obtain the first person object image obtained in the storage area, and bind the first key object image and the first person object image;

[0009] Sending a task list to the terminal to which the first person object image belongs, the task list including vehicle information;

[0010] In response to a recycling instruction issued by the storage area, acquiring a second key object image and a second person object image at the storage area;

[0011] Comparing the first key object image and the second key object image to obtain a first comparison result;

[0012] Comparing the first person object image with the second person object image to obtain a second comparison result;

[0013] When the first comparison result and the second comparison result are both consistent, closing the storage area;

[0014] Wherein, when comparing the first key object image, the second key object image, the first person object image and the second person object image, structured light is used to determine the three-dimensional information.

[0015] In a possible implementation manner of the first aspect, comparing the first key object image with the second key object image includes:

[0016] extracting pattern features on the first key object image;

[0017] A feature reference line is randomly established on the pattern feature, and the intersection of the feature reference line and the pattern feature is recorded as a feature reference point. There are at least two feature reference points on one feature reference line;

[0018] Use the characteristic reference points to establish a characteristic grid, and the number of edges of each grid in the characteristic grid is the same;

[0019] reconstructing a feature grid on the second key object image;

[0020] Wherein, when the feature grid is successfully reconstructed on the second key object image, the first comparison result is consistent, otherwise the first comparison result is inconsistent;

[0021] There are multiple feature reference lines and at least two feature reference lines intersect.

[0022] In a possible implementation manner of the first aspect, before reconstructing the feature grid on the second key object image, the method further includes:

[0023] placing the first key object image and the second key object image onto the same image;

[0024] The position of the vehicle key on the second key object image is corrected according to the movement amount so that the movement amount is less than or equal to the allowable movement amount.

[0025] In a possible implementation manner of the first aspect, the method further includes determining a height change of the feature grid, where the determining the height change of the feature grid includes:

[0026] Projecting a light spot on a feature reference line;

[0027] Fixing an analysis direction on the characteristic reference line and determining the variation of the spacing between adjacent light spots in the analysis direction;

[0028] Assign direction vectors to feature reference points based on the spacing changes.

[0029] In a possible implementation manner of the first aspect, determining the height change area according to the spacing change includes:

[0030] Determine the initial height of one endpoint of the feature reference line;

[0031] Get the difference sequence of the distances between adjacent light spots at the initial height;

[0032] Compare and analyze the change in the spacing between adjacent light spots in the direction with the difference series to determine the height change area.

[0033] In a possible implementation manner of the first aspect, when the height change region does not exist, the characteristic reference line is adjusted until the height change region appears on the characteristic reference line.

[0034] In a possible implementation manner of the first aspect, when comparing the first person object image with the second person object image, the step further includes:

[0035] Establishing rectangular projection areas on the first person object image and the second person object image respectively;

[0036] Get the projection point on the rectangular projection area;

[0037] Draw a difference curve or a quadratic difference curve based on the spacing between adjacent projection points;

[0038] Comparing a difference curve on the first person object image with a corresponding difference curve on the second person object image or comparing a quadratic difference curve on the first person object image with a corresponding quadratic difference curve on the second person object image;

[0039] When the second comparison result is consistent, it is required that the difference curve on the first person object image and the corresponding difference curve on the second person object image are similar, or the secondary difference curve on the first person object image and the corresponding secondary difference curve on the second person object image are similar.

[0040] In a second aspect, the present application provides a comparative authentication device based on image measurement, comprising:

[0041] A first acquisition unit, configured to acquire, in response to a received task order, a first key object image of a storage area pointed to by storage information in the task order;

[0042] A second acquisition unit, used to continue to acquire the first person object image obtained in the storage area, and bind the first key object image and the first person object image;

[0043] A first communication unit is used to send a task list to the terminal to which the first person object image belongs, wherein the task list includes vehicle information;

[0044] a third acquisition unit, configured to acquire a second key object image and a second person object image at the storage area in response to a recycling instruction issued by the storage area;

[0045] A first comparison unit, used for comparing the first key object image with the second key object image to obtain a first comparison result;

[0046] A second comparison unit, used for comparing the first person object image with the second person object image to obtain a second comparison result;

[0047] A second communication unit, configured to close the storage area when the first comparison result and the second comparison result are both consistent;

[0048] Wherein, when comparing the first key object image, the second key object image, the first person object image and the second person object image, structured light is used to determine the three-dimensional information.

[0049] In a third aspect, the present application provides an operation management system, the system comprising:

[0050] one or more memories for storing instructions; and

[0051] One or more processors, used to call and run the instructions from the memory to execute the method as described in the first aspect and any possible implementation of the first aspect.

[0052] In a fourth aspect, the present application provides a computer-readable storage medium, the computer-readable storage medium comprising:

[0053] Program, when the program is executed by a processor, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0054] In a fifth aspect, the present application provides a computer program product, comprising program instructions. When the program instructions are executed by a computing device, the method described in the first aspect and any possible implementation of the first aspect is executed.

[0055] In a sixth aspect, the present application provides a chip system, which includes a processor for implementing the functions involved in the above aspects, for example, generating, receiving, sending, or processing the data and / or information involved in the above methods.

[0056] The chip system may be composed of chips, or may include chips and other discrete devices.

[0057] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wired or wireless means, or the processor and the memory can also be coupled on the same device. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a schematic flowchart of the steps of a car washing method provided in this application.

[0059] Figure 2 It is a process schematic diagram of a car washing method provided by the present application.

[0060] Figure 3 It is a schematic diagram provided by the present application for establishing feature reference lines and feature reference points.

[0061] Figure 4 It is a schematic diagram of a characteristic grid provided in this application.

[0062] Figure 5 It is a schematic diagram of a movement amount provided by this application.

[0063] Figure 6 This is a schematic diagram of a standard spacing between adjacent light spots provided in this application.

[0064] Figure 7 is based on Figure 6 Schematic diagram of the change in spacing between adjacent light spots.

[0065] Figure 8 It is a schematic diagram of establishing a rectangular projection area provided by the present application. DETAILED DESCRIPTION

[0066] The technical solution in this application is further described in detail below in conjunction with the accompanying drawings.

[0067] This application discloses a comparative authentication method based on image measurement, please refer to Figure 1 In some examples, the image measurement-based comparative authentication method disclosed in this application includes the following steps:

[0068] S101, in response to a received task order, obtaining a first key object image of a storage area pointed to by storage information in the task order;

[0069] S102, continue to obtain the first person object image obtained in the storage area, and bind the first key object image and the first person object image;

[0070] S103, sending a task list to the terminal to which the first person object image belongs, the task list including vehicle information;

[0071] S104, in response to a recycling instruction issued by the storage area, acquiring a second key object image and a second person object image at the storage area;

[0072] S105, comparing the first key object image and the second key object image to obtain a first comparison result;

[0073] S106, comparing the first person object image and the second person object image to obtain a second comparison result;

[0074] S107, when the first comparison result and the second comparison result are both consistent, closing the storage area;

[0075] Wherein, when comparing the first key object image, the second key object image, the first person object image and the second person object image, structured light is used to determine the three-dimensional information.

[0076] In order to more clearly understand the technical solution in this application, the relevant contents are first introduced.

[0077] The water consumption of a car wash is generally around 190-200 liters. If automated washing equipment is used, the water consumption will increase further. As for the type of water used, only recycled water can be used. At the same time, considering environmental impact factors and environmental protection requirements, the cost of car washing in urban areas has increased year by year.

[0078] Based on this, door-to-door car washing began to be accepted by the market. The advantage of door-to-door car washing is that car owners save travel and waiting time, and the advantage in time cost is very obvious, but there are disadvantages in equipment, water consumption and site management, and due to the dispersion of customers, the travel cost is too high.

[0079] The technical solution in this application chooses to implement car washing in a non-fixed location within an area, such as a parking lot. After the user places the vehicle at the designated location, the user places the vehicle key in a storage cabinet on one side and places an order. After receiving the order, the staff takes the vehicle key, then moves the vehicle and washes it, and then returns the vehicle to its original location after the washing is completed.

[0080] This method can concentrate the customer base, solve the problem of high travel costs, and does not require fixed sites and fixed equipment. Water consumption can be effectively controlled through micro-water car washing and waterless car washing.

[0081] In general, the image measurement-based comparative authentication method disclosed in this application involves software and hardware such as a server, a storage cabinet, a client app, and an employee app. The user issues a demand form on the client app, and the server issues a task form to the storage cabinet and the employee app after receiving the demand form. Figure 2 shown.

[0082] After the storage cabinet opens the designated single storage box, the user puts the vehicle key into the opened single storage box and closes the door of the single storage box. The employee who receives the task order arrives at the storage cabinet and opens the single storage box to get the vehicle key, washes the vehicle, and puts the vehicle key back into the single storage box after washing is completed, completing the vehicle washing task.

[0083] There are two advantages to getting the vehicle keys. The first advantage is that you can move the vehicle, making it easier to clean around it. The second advantage is that you can clean the vehicle's interior.

[0084] In step S101 and step S102, in response to the received task order, the first key object image of the storage area pointed to by the storage information in the task order is obtained. After obtaining the first key object image, the first person object image obtained in the storage area is continued to be obtained, and the first key object image and the first person object image are bound.

[0085] At this point, the vehicle key (first key object) can be bound to the staff member (first staff member object), and after the vehicle cleaning task is completed, the same staff member is required to return it.

[0086] In step S103, a task list is sent to the terminal to which the first person object image belongs. The task list includes vehicle information, including a front face photo of the vehicle, a license plate number, and a parking space number, etc., in order to facilitate staff to quickly find the vehicle that needs to be cleaned.

[0087] After obtaining the vehicle information, the staff (first person object) finds the vehicle and cleans the exterior and interior of the vehicle. Photos are taken using the employee app before, during, and after cleaning. There are no restrictions on the number and location of photos taken.

[0088] In step S104, in response to a recovery instruction issued by the storage area, a second key object image and a second person object image at the storage area are obtained, and then in step S105, the first key object image and the second key object image are compared to obtain a first comparison result; in step S106, the first person object image and the second person object image are compared to obtain a second comparison result.

[0089] The first comparison result is used to determine the consistency of the vehicle key, and the second comparison result is used to determine the consistency of the staff. When the first comparison result and the second comparison result are both consistent, the storage area is closed, that is, the content in step S107.

[0090] When comparing the first key object image, the second key object image, the first person object image and the second person object image, structured light is used to determine three-dimensional information. The three-dimensional information can determine that the vehicle key and the staff are both three-dimensional, that is, it is impossible to deceive the consistency of the first comparison result and the second comparison result by taking photos.

[0091] In some examples, the specific manner of comparing the first key object image and the second key object image is:

[0092] S201, extracting pattern features from a first key object image;

[0093] S202, randomly establishing a feature reference line on the pattern feature, and recording the intersection of the feature reference line and the pattern feature as a feature reference point. There are at least two feature reference points on one feature reference line;

[0094] S203, using the characteristic reference points to establish a characteristic grid, wherein the number of edges of each grid in the characteristic grid is the same;

[0095] S204, reconstructing a feature grid on the second key object image;

[0096] Wherein, when the feature grid is successfully reconstructed on the second key object image, the first comparison result is consistent, otherwise the first comparison result is inconsistent;

[0097] There are multiple feature reference lines and at least two feature reference lines intersect.

[0098] In step S201 to step S204, pattern features are first extracted from the first key object image, and then feature reference lines are randomly established on the pattern features. Figure 3 As shown, the intersection of the feature reference line and the pattern feature is recorded as the feature reference point, there are at least two feature reference points on one feature reference line, there are multiple feature reference lines and at least two feature reference lines intersect.

[0099] In some possible implementations, the pattern feature refers to a button on a car, a pattern on the button, an edge of the button, and the like.

[0100] In some possible implementations, when establishing a feature reference line, edge points on the pattern feature or endpoints inside the pattern feature are selected.

[0101] Then use the feature reference points to create a feature grid. Figure 4 As shown, the number of edges of each grid in the feature grid is the same, and a feature grid generated based on the first key object image is obtained.

[0102] Then, the feature grid is reconstructed on the second key object image. When the reconstruction is successful, the first comparison result is consistent, otherwise the first comparison result is inconsistent.

[0103] This processing method uses multiple pattern features on the first key object image and considers the geometric relationship between the pattern features.

[0104] Before reconstructing the feature grid on the second key object image, the following steps are added:

[0105] S301, placing a first key object image and a second key object image on the same image;

[0106] S302, determining a movement amount according to relative positions of a first key object image and a second key object image on the same image;

[0107] S303: Correct the position of the vehicle key on the second key object image according to the movement amount so that the movement amount is less than or equal to the allowable movement amount.

[0108] The contents of step S301 and step S302 are mainly to take into account that the inconsistency between the positions where the user places the vehicle key and the staff places the vehicle key will cause image distortion and lead to misjudgment. The specific method of correcting the position of the vehicle key on the second key object image according to the movement amount is to use a light to project a visible light in the storage box. When the user places the key, the center line of the key needs to coincide with the visible light as much as possible.

[0109] When the overlap does not meet the requirements, the user is prompted to adjust the placement of the vehicle key.

[0110] In some examples, the method further includes determining a height variation of a feature grid, where the height variation of the feature grid refers to the feature grid having features in a three-dimensional space, because feature reference points on the feature grid are not distributed on the same plane.

[0111] At this time, if the feature grid is given a height change, the feature grid can be made authentic, because the comparison in two-dimensional space can be deceived through the form of a photo.

[0112] The specific method for determining the height change of the feature grid is as follows:

[0113] Projecting a light spot on a feature reference line;

[0114] Fixing an analysis direction on the characteristic reference line and determining the variation of the spacing between adjacent light spots in the analysis direction;

[0115] Assign direction vectors to feature reference points based on the spacing changes.

[0116] See also Figure 6 and Figure 7 It should be understood that if the characteristic reference line is a straight line, then under the premise of known height, the change in spacing between adjacent light spots (increase, decrease) is clear, but when the characteristic reference line is a curve, the change in spacing between adjacent light spots will be abnormal (increase or decrease). The abnormality can be used to determine whether the characteristic reference line at the position corresponding to the abnormality has an upward trend or a downward trend.

[0117] At this time, the direction vector can be assigned to the feature reference point, that is, the feature reference point has a spatial feature, the direction of the direction vector is determined according to increase or decrease, and the length of the direction vector is assigned according to the length difference.

[0118] When determining the height change area based on the spacing change, use the following method:

[0119] S401, determining an initial height of an end point of a feature reference line;

[0120] S402, obtaining a difference sequence corresponding to the distances between adjacent light spots at the initial height;

[0121] S403, comparing and analyzing the change in the spacing between adjacent light spots in the direction and the difference series to determine a height change area.

[0122] In step S401 to step S403, it is first necessary to determine the initial height of an endpoint of the feature reference line. The initial height here refers to the height of the position of the light spot (an endpoint of the feature reference line). One way to achieve this is to use a binocular vision algorithm for calculation.

[0123] Then, the difference series (intrinsic parameters) corresponding to the distances between adjacent light spots at the initial height are used. The role of the initial height is to determine the reference value of the distance between adjacent light spots. Only through this reference value can the corresponding difference series be determined.

[0124] Finally, the distance change between adjacent light spots in the analysis direction is compared with the difference series. The comparison process is referenced Figure 7 , determine the height change area, which refers to the place where the distance change between adjacent light spots does not match the difference series.

[0125] In some possible implementations, when the height variation region does not exist, the feature reference line is adjusted until the height variation region appears on the feature reference line.

[0126] In some examples, when comparing the first person object image and the second person object image, the following processing is used:

[0127] S501, establishing rectangular projection areas on the first person object image and the second person object image respectively;

[0128] S502, obtaining projection points on the rectangular projection area;

[0129] S503, drawing a difference curve or a quadratic difference curve based on the distance between adjacent projection points;

[0130] S504, comparing a difference curve on the first person object image with a corresponding difference curve on the second person object image or comparing a quadratic difference curve on the first person object image with a corresponding quadratic difference curve on the second person object image;

[0131] When the second comparison result is consistent, it is required that the difference curve on the first person object image and the corresponding difference curve on the second person object image are similar, or the secondary difference curve on the first person object image and the corresponding secondary difference curve on the second person object image are similar.

[0132] In step S501 to step S504, rectangular projection areas are established on the first person object image and the second person object image respectively. Figure 8 As shown, the projection points on the rectangular projection area are then obtained, and then a difference curve or a quadratic difference curve is drawn based on the spacing between adjacent projection points.

[0133] Compare the difference curve on the first person object image with the corresponding difference curve on the second person object image, or compare the quadratic difference curve on the first person object image with the corresponding quadratic difference curve on the second person object image. When the difference curve on the first person object image and the corresponding difference curve on the second person object image are similar, the second comparison result is consistent.

[0134] Similarity means that when one of the difference curves or the quadratic difference curves is subjected to any one or more of movement (X-axis, Y-axis), stretching (X-axis, Y-axis) and compression (X-axis, Y-axis), the two corresponding difference curves or the quadratic difference curves can overlap, or the area of ​​the closed region formed is within the allowable range.

[0135] Of course, before this, it is necessary to first compare the first person object image and the second person object image in the face recognition process. The contents of steps S501 to S505 in this application are performed when the face recognition process is completed and the result is passed. The purpose is to avoid the staff using pictures instead of real people to generate the second person object image.

[0136] The present application also provides a comparative authentication device based on image measurement, comprising:

[0137] A first acquisition unit, configured to acquire, in response to a received task order, a first key object image of a storage area pointed to by storage information in the task order;

[0138] A second acquisition unit, used to continue to acquire the first person object image obtained in the storage area, and bind the first key object image and the first person object image;

[0139] A first communication unit is used to send a task list to the terminal to which the first person object image belongs, wherein the task list includes vehicle information;

[0140] a third acquisition unit, configured to acquire a second key object image and a second person object image at the storage area in response to a recycling instruction issued by the storage area;

[0141] A first comparison unit, used for comparing the first key object image with the second key object image to obtain a first comparison result;

[0142] A second comparison unit, used for comparing the first person object image with the second person object image to obtain a second comparison result;

[0143] A second communication unit, configured to close the storage area when the first comparison result and the second comparison result are both consistent;

[0144] Wherein, when comparing the first key object image, the second key object image, the first person object image and the second person object image, structured light is used to determine the three-dimensional information.

[0145] Furthermore, it also includes:

[0146] A pattern feature extraction unit, used to extract pattern features from the first key object image;

[0147] A feature reference line establishing unit, used to randomly establish a feature reference line on the pattern feature, wherein the intersection of the feature reference line and the pattern feature is recorded as a feature reference point, and there are at least two feature reference points on one feature reference line;

[0148] A feature grid establishment unit is used to establish a feature grid using a feature reference point, wherein the number of edges of each grid in the feature grid is the same;

[0149] A feature grid reconstruction unit, used for reconstructing a feature grid on the second key object image;

[0150] Wherein, when the feature grid is successfully reconstructed on the second key object image, the first comparison result is consistent, otherwise the first comparison result is inconsistent;

[0151] There are multiple feature reference lines and at least two feature reference lines intersect.

[0152] Furthermore, it also includes:

[0153] An image processing unit, configured to place the first key object image and the second key object image onto the same image;

[0154] a movement amount determining unit, configured to determine the movement amount according to the relative positions of the first key object image and the second key object image on the same image;

[0155] The position correction unit is used to correct the position of the vehicle key on the second key object image according to the movement amount so that the movement amount is less than or equal to the allowed movement amount.

[0156] Furthermore, it also includes:

[0157] A light spot processing unit, used for projecting light spots on a feature reference line;

[0158] A spacing analysis unit, used to fix an analysis direction on the characteristic reference line and determine the spacing variation between adjacent light spots in the analysis direction;

[0159] The direction vector assigning unit is used to assign a direction vector to a feature reference point according to a change in spacing.

[0160] Furthermore, it also includes:

[0161] An initial height determination unit, used to determine an initial height of an end point of a feature reference line;

[0162] A parameter acquisition unit, used to obtain a difference series corresponding to the distances between adjacent light spots at the initial height;

[0163] The numerical comparison unit is used to compare the change in the spacing between adjacent light spots in the analysis direction with the difference series to determine the height change area.

[0164] Further, when the height change region does not exist, the characteristic reference line is adjusted until the height change region appears on the characteristic reference line.

[0165] Furthermore, it also includes:

[0166] A projection area establishing unit, used to establish rectangular projection areas on the first person object image and the second person object image respectively;

[0167] A projection point acquisition unit, used to acquire projection points on a rectangular projection area;

[0168] A curve receipt unit, used for drawing a difference curve or a quadratic difference curve based on the spacing between adjacent projection points;

[0169] A curve comparison unit, used to compare a difference curve on the first person object image with a corresponding difference curve on the second person object image or to compare a quadratic difference curve on the first person object image with a corresponding quadratic difference curve on the second person object image;

[0170] When the second comparison result is consistent, it is required that the difference curve on the first person object image and the corresponding difference curve on the second person object image are similar, or the secondary difference curve on the first person object image and the corresponding secondary difference curve on the second person object image are similar.

[0171] In one example, the unit in any of the above devices can be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASICs), or, one or more digital signal processors (DSPs), or, one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0172] For another example, when the units in the device can be implemented in the form of a processing element scheduling program, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0173] Various objects such as various messages / information / equipment / network elements / systems / devices / actions / operations / processes / concepts that may appear in this application are named. It can be understood that these specific names do not constitute a limitation on the relevant objects. The names assigned may change with factors such as scenarios, contexts or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from the functions and technical effects embodied / executed in the technical scheme.

[0174] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0175] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0176] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0177] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0178] It should also be understood that in various embodiments of the present application, the first, second, etc. are only used to indicate that multiple objects are different. For example, the first time window and the second time window are only used to indicate different time windows. They should not have any impact on the time window itself, and the first, second, etc. mentioned above should not impose any limitations on the embodiments of the present application.

[0179] It should also be understood that in the various embodiments of the present application, unless otherwise specified or there is a logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced to each other, and the technical features in different embodiments can be combined to form new embodiments according to their internal logical relationships.

[0180] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a computer-readable storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned computer-readable storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0181] The present application also provides an operation management system, the system comprising:

[0182] one or more memories for storing instructions; and

[0183] One or more processors are used to call and run the instructions from the memory to execute the method as described above.

[0184] The present application also provides a computer program product, which includes instructions. When the instructions are executed, the terminal device and the network device perform operations of the terminal device and the network device corresponding to the above method.

[0185] The present application also provides a chip system, which includes a processor for implementing the functions involved in the above content, such as generating, receiving, sending, or processing the data and / or information involved in the above method.

[0186] The chip system may be composed of chips, or may include chips and other discrete devices.

[0187] The processor mentioned in any of the above places can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for executing programs for controlling the above-mentioned feedback information transmission method.

[0188] In a possible design, the chip system also includes a memory, which is used to store necessary program instructions and data. The processor and the memory can be decoupled and respectively set on different devices, connected by wire or wireless means to support the chip system to implement various functions in the above embodiments. Alternatively, the processor and the memory can also be coupled on the same device.

[0189] Optionally, the computer instructions are stored in a memory.

[0190] Optionally, the memory is a storage unit within the chip, such as a register, a cache, etc. The memory can also be a storage unit within the terminal located outside the chip, such as a ROM or other types of static storage devices that can store static information and instructions, RAM, etc.

[0191] It can be understood that the memory in the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories.

[0192] The non-volatile memory may be a ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory.

[0193] The volatile memory may be a RAM, which is used as an external cache. There are many different types of RAM, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct memory bus RAM.

[0194] The embodiments of this specific implementation method are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Therefore, all equivalent changes made based on the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A comparative authentication method based on image measurement, characterized in that: include: In response to the received task order, acquiring a first key object image of a storage area pointed to by storage information in the task order; Continue to obtain the first person object image obtained in the storage area, and bind the first key object image and the first person object image; Sending a task list to the terminal to which the first person object image belongs, the task list including vehicle information; In response to a recycling instruction issued by the storage area, acquiring a second key object image and a second person object image at the storage area; Comparing the first key object image and the second key object image to obtain a first comparison result; Comparing the first person object image with the second person object image to obtain a second comparison result; When the first comparison result and the second comparison result are both consistent, closing the storage area; wherein, when comparing the first key object image, the second key object image, the first person object image, and the second person object image, structured light is used to determine the three-dimensional information; Comparing the first key object image and the second key object image includes: extracting pattern features on the first key object image; A feature reference line is randomly established on the pattern feature, and the intersection of the feature reference line and the pattern feature is recorded as a feature reference point. There are at least two feature reference points on one feature reference line; Use the characteristic reference points to establish a characteristic grid, and the number of edges of each grid in the characteristic grid is the same; reconstructing a feature grid on the second key object image; Wherein, when the feature grid is successfully reconstructed on the second key object image, the first comparison result is consistent, otherwise the first comparison result is inconsistent; There are multiple feature reference lines and at least two feature reference lines intersect.

2. The image measurement-based comparative authentication method according to claim 1, characterized in that: Before reconstructing the feature grid on the second key object image, the method further includes: placing the first key object image and the second key object image onto the same image; determining the amount of movement based on the relative positions of the first key object image and the second key object image on the same image; The position of the vehicle key on the second key object image is corrected according to the movement amount so that the movement amount is less than or equal to the allowable movement amount.

3. The image measurement-based comparative authentication method according to claim 2, characterized in that: It also includes determining the height change of the feature grid, and determining the height change of the feature grid includes: Projecting a light spot on a feature reference line; Fixing an analysis direction on the characteristic reference line and determining the variation of the spacing between adjacent light spots in the analysis direction; Assign direction vectors to feature reference points based on the spacing changes.

4. The image measurement-based comparative authentication method according to claim 3, characterized in that: When determining the height change area based on the spacing change, include: Determine the initial height of one endpoint of the feature reference line; Get the difference sequence of the distances between adjacent light spots at the initial height; Compare and analyze the change in the spacing between adjacent light spots in the direction with the difference series to determine the height change area.

5. The image measurement-based comparative authentication method according to claim 4, characterized in that: When the height change area does not exist, adjust the feature reference line until the height change area appears on the feature reference line.

6. The image measurement-based comparative authentication method according to claim 1, characterized in that: When comparing the first person object image and the second person object image, the process further includes: Establishing rectangular projection areas on the first person object image and the second person object image respectively; Get the projection point on the rectangular projection area; Draw a difference curve or a quadratic difference curve based on the spacing between adjacent projection points; Comparing a difference curve on the first person object image with a corresponding difference curve on the second person object image or comparing a quadratic difference curve on the first person object image with a corresponding quadratic difference curve on the second person object image; When the second comparison result is consistent, it is required that the difference curve on the first person object image and the corresponding difference curve on the second person object image are similar, or the secondary difference curve on the first person object image and the corresponding secondary difference curve on the second person object image are similar.

7. A comparative authentication device based on image measurement, characterized in that: include: A first acquisition unit, configured to acquire, in response to a received task order, a first key object image of a storage area pointed to by storage information in the task order; A second acquisition unit, used to continue to acquire the first person object image obtained in the storage area, and bind the first key object image and the first person object image; A first communication unit is used to send a task list to the terminal to which the first person object image belongs, wherein the task list includes vehicle information; a third acquisition unit, configured to acquire a second key object image and a second person object image at the storage area in response to a recycling instruction issued by the storage area; A first comparison unit, used for comparing the first key object image with the second key object image to obtain a first comparison result; A second comparison unit, used for comparing the first person object image with the second person object image to obtain a second comparison result; A second communication unit, configured to close the storage area when the first comparison result and the second comparison result are both consistent; wherein, when comparing the first key object image, the second key object image, the first person object image, and the second person object image, structured light is used to determine the three-dimensional information; Comparing the first key object image and the second key object image includes: extracting pattern features on the first key object image; A feature reference line is randomly established on the pattern feature, and the intersection of the feature reference line and the pattern feature is recorded as a feature reference point. There are at least two feature reference points on one feature reference line; Use the characteristic reference points to establish a characteristic grid, and the number of edges of each grid in the characteristic grid is the same; reconstructing a feature grid on the second key object image; Wherein, when the feature grid is successfully reconstructed on the second key object image, the first comparison result is consistent, otherwise the first comparison result is inconsistent; There are multiple feature reference lines and at least two feature reference lines intersect.

8. An operation management system, characterized in that: The system comprises: one or more memories for storing instructions; and One or more processors, configured to call and execute the instructions from the memory to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer readable storage medium comprises: The program, when the program is executed by a processor, the method according to any one of claims 1 to 6 is executed.

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