CN108596047A - Vehicle damages recognition methods, intelligent terminal and computer readable storage medium - Google Patents
Vehicle damages recognition methods, intelligent terminal and computer readable storage medium Download PDFInfo
- Publication number
- CN108596047A CN108596047A CN201810292585.7A CN201810292585A CN108596047A CN 108596047 A CN108596047 A CN 108596047A CN 201810292585 A CN201810292585 A CN 201810292585A CN 108596047 A CN108596047 A CN 108596047A
- Authority
- CN
- China
- Prior art keywords
- vehicle
- damage
- accident
- photo
- accident vehicle
- 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
- 238000000034 method Methods 0.000 title claims abstract description 55
- 238000012423 maintenance Methods 0.000 claims description 25
- 238000004590 computer program Methods 0.000 claims description 6
- 238000013459 approach Methods 0.000 claims description 4
- 230000008569 process Effects 0.000 abstract description 4
- 238000012790 confirmation Methods 0.000 abstract 1
- 238000012545 processing Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000007423 decrease Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 210000001320 hippocampus Anatomy 0.000 description 1
- 230000004297 night vision Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Accounting & Taxation (AREA)
- Multimedia (AREA)
- Finance (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- General Business, Economics & Management (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present embodiments relate to automotive field, a kind of vehicle damage recognition methods, intelligent terminal and computer readable storage medium are disclosed.In the present invention, the vehicle damage photo of accident vehicle and the model of accident vehicle are obtained；Vehicle photo corresponding with model is obtained according to the model of accident vehicle；Photo is damaged according to vehicle and vehicle photo determines that type is damaged at the vehicle damage position of accident vehicle and vehicle；According to the vehicle damage information of accident vehicle and pre-set vehicle damage information and the correspondence for waiting for indemnity, determine accident vehicle waits for indemnity, wherein the vehicle damage information of accident vehicle includes at least：Model, vehicle damage position and the vehicle of accident vehicle damage type.Can automatic identification vehicle damage, confirmation waits for indemnity, and process accident is convenient, fast, while providing Claims Resolution foundation for driving new hand, reduces cheated probability, raising user experience.
Description
Technical Field
The embodiment of the invention relates to the field of automobiles, in particular to a vehicle damage identification method, an intelligent terminal and a computer readable storage medium.
Background
With the development of urbanization, the role of automobiles in daily life of people is becoming more and more important. However, as the number of automobiles increases, the safety problem of driving automobiles is more and more emphasized, but driving accidents still occur in a large number. At present, a driving accident handling method is more and more perfect, if a large accident occurs, an alarm is given immediately under the condition of confirming the safety of personnel, evidence is reserved, and the evidence is reported to an insurance company; when minor accidents happen, people generally prefer to solve the problems privately; and if the agreement cannot be achieved, alarming.
The inventor finds that at least the following problems exist in the prior art: the existing accident handling method is slow in speed, and if a novice driving on the road encounters a small accident, the price to be compensated is not clear, so that the accident handling method is easy to deceive by people.
Disclosure of Invention
An object of an embodiment of the present invention is to provide a car damage recognition method, an intelligent terminal, and a computer-readable storage medium, which can automatically recognize car damage, determine an amount to be compensated, and handle an accident conveniently and quickly, and meanwhile, provide a basis for settlement of an accident, reduce the probability of being deceived, and improve user experience.
In order to solve the technical problem, an embodiment of the present invention provides a vehicle damage identification method, including: acquiring a car damage picture of an accident car and the model of the accident car; acquiring a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle; determining the vehicle damage part and the vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture; determining the amount of money to be reimbursed of the accident vehicle according to the vehicle damage information of the accident vehicle and the preset corresponding relationship between the vehicle damage information and the amount of money to be reimbursed, wherein the vehicle damage information of the accident vehicle at least comprises the following steps: the type, the damage part and the damage type of the accident vehicle.
An embodiment of the present invention further provides an intelligent terminal, including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the vehicle damage identification method.
The embodiment of the invention also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the vehicle damage identification method.
Compared with the prior art, the method and the device for detecting the accident vehicle damage acquire the vehicle damage picture of the accident vehicle and the model of the accident vehicle; acquiring a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle; determining the vehicle damage part and the vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture; determining the amount of money to be reimbursed of the accident vehicle according to the vehicle damage information of the accident vehicle and the preset corresponding relationship between the vehicle damage information and the amount of money to be reimbursed, wherein the vehicle damage information of the accident vehicle at least comprises the following steps: the type, the damage part and the damage type of the accident vehicle. According to the car damage photo and the car photo, the car damage position and the car damage type are automatically determined, car damage information is provided for the follow-up automatic determination of the amount of money to be reimbursed, according to the obtained car damage information and the preset corresponding relation, the amount of money to be reimbursed of the accident car is automatically determined, a small accident does not need to be helped by a professional, car damage is automatically recognized, the amount of money to be reimbursed is confirmed, the method is convenient and fast, simultaneously, an indemnification basis is provided for a car driving novice, the probability of cheating is reduced, and user experience is improved.
In addition, the method for acquiring the car damage photo of the accident car specifically comprises the following steps: and acquiring a car damage picture of the accident vehicle through an infrared camera or a three-dimensional camera. Through infrared camera or three-dimensional camera, the car that shoots decreases the photo more clear for the result of car loss discernment is more accurate.
In addition, according to the car damage picture and the car picture, the car damage part and the car damage type of the accident car are determined, and the method specifically comprises the following steps: determining the vehicle damage part of the accident vehicle according to the vehicle damage picture; acquiring a first characteristic parameter of the car damage photo and a second characteristic parameter of the car damage photo, wherein the first characteristic parameter at least comprises the following steps: the shape and the color of the car damage part, the second characteristic parameters at least comprise: the shape and color of the corresponding part in the vehicle picture; and determining the vehicle damage type of the accident vehicle according to the first characteristic parameter and the second characteristic parameter. Provided is an embodiment for determining a vehicle damage location and a vehicle damage type according to a vehicle damage picture and a color and a shape in the vehicle damage picture.
In addition, the car damage photo specifically includes: close-up photos of the car damage part of the accident car and panoramic photos containing the car damage part of the accident car; determining the vehicle damage part of the accident vehicle according to the vehicle damage picture, which specifically comprises the following steps: recognizing the vehicle damage part of the accident vehicle in the panoramic picture; obtaining a first characteristic parameter of the car damage photo, specifically: a first feature parameter of the close-up photograph is acquired. The vehicle damage part is obtained according to the panoramic photo, the first characteristic parameter is determined according to the close-up photo, and different photos are respectively selected to obtain different vehicle damage information, so that the obtained vehicle damage information is more accurate, and the accuracy of a vehicle damage identification result is further ensured.
In addition, after determining the amount to be compensated for the accident vehicle, the method further comprises the following steps: judging whether the amount to be compensated is larger than a preset threshold value or not; when the amount to be compensated is judged to be larger than the preset threshold value, sending out prompt information for advising the user to walk insurance maintenance approaches; and when the amount to be compensated is judged not to be larger than the preset threshold value, sending out prompt information for recommending the user to solve privately. According to the different determined amounts to be compensated, different processing schemes are provided for the user, and the user experience is improved.
In addition, after determining the amount to be compensated of the accident vehicle, the method further comprises the following steps: and providing information of maintenance points in a preset range of the accident vehicle for a user to make an appointment for maintenance. After the amount to be compensated is determined, the information of the maintenance points in the preset range of the accident vehicle is provided for the user, the user can directly reserve maintenance according to the information of the maintenance points, the use of the user is facilitated, and the user experience is further improved.
In addition, before the car damage picture of the accident vehicle is obtained, the method further comprises the following steps: sending out prompt information for prompting a user to correctly shoot the car damage picture, wherein the prompt information at least comprises: when the panoramic photo is shot, the damaged part of the car needs to be framed, the correct angle for shooting the panoramic photo and the correct angle for shooting the close-up photo. Before the user obtains the car damage photo, the user is prompted how to shoot the panoramic photo and the close-up photo, the user is guided to shoot the correct car damage photo, operation guidance is provided for the user, and therefore user experience is improved.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the figures in which like reference numerals refer to similar elements and which are not to scale unless otherwise specified.
Fig. 1 is a detailed flowchart of a vehicle damage recognition method according to a first embodiment of the present invention;
fig. 2 is a detailed flowchart of a vehicle damage recognition method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an intelligent terminal according to a third embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those of ordinary skill in the art that numerous technical details are set forth in order to provide a better understanding of the present application in various embodiments of the present invention. However, the technical solution claimed in the present application can be implemented without these technical details and various changes and modifications based on the following embodiments.
A first embodiment of the present invention relates to a vehicle damage recognition method. The core of the embodiment lies in obtaining the car damage picture of the accident vehicle and the model of the accident vehicle; acquiring a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle; determining the vehicle damage part and the vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture; determining the amount of money to be reimbursed of the accident vehicle according to the vehicle damage information of the accident vehicle and the preset corresponding relationship between the vehicle damage information and the amount of money to be reimbursed, wherein the vehicle damage information of the accident vehicle at least comprises the following steps: the type, the damage part and the damage type of the accident vehicle. According to the car damage photo and the car photo, the car damage position and the car damage type are automatically determined, car damage information is provided for the follow-up automatic determination of the amount of money to be reimbursed, according to the obtained car damage information and the preset corresponding relation, the amount of money to be reimbursed of the accident car is automatically determined, a small accident does not need to be helped by a professional, car damage is automatically recognized, the amount of money to be reimbursed is confirmed, the method is convenient and fast, simultaneously, an indemnification basis is provided for a car driving novice, the probability of cheating is reduced, and user experience is improved. The following describes implementation details of the vehicle damage recognition method according to the present embodiment in detail, and the following description is only provided for easy understanding and is not necessary to implement the present embodiment.
The vehicle damage identification method in the embodiment can be applied to intelligent terminals, such as mobile phones, iPads and other portable intelligent terminals, and can also be applied to systems with display equipment and shooting functions. A specific flowchart of the vehicle damage identification method in the present embodiment is shown in fig. 1, and specifically includes:
step 101: and acquiring a car damage picture of the accident vehicle and the model of the accident vehicle.
Specifically, a car damage picture of the accident vehicle is obtained through an infrared camera or a three-dimensional camera. Because infrared camera adopts the infrared ray to shoot, compare in ordinary camera, infrared camera has the advantage such as high definition, night vision distance are far away, and the car of the accident vehicle that shoots decreases the photo and compare in the photo that ordinary camera was shot more clearly. And the three-dimensional camera is used, and the car damage picture shot by using the three-dimensional camera shooting technology is more stereoscopic, so that the abnormal part of the accident car can be seen more visually. The infrared camera or the three-dimensional camera is used for enabling the shot picture to be clearer or stereoscopic, so that the subsequent car damage picture can be identified conveniently, and the accuracy of the car damage identification result is improved.
The model of the accident vehicle is obtained through the following modes: acquiring the model of an accident vehicle manually input by a user; or acquiring a head photo or a tail photo of the accident vehicle, and determining the type of the accident vehicle according to the head photo or the tail photo. Specifically, the user may be prompted to enter the model of the accident vehicle, such as: a hippocampus 323. The method comprises the steps of shooting a picture of the tail of a vehicle through a tail camera, or shooting a picture of the head or the tail of the vehicle through an intelligent terminal or a camera device, and matching the obtained picture of the head or the tail of the vehicle with a picture obtained by a network side, so as to determine the type of an accident vehicle.
Step 102: and obtaining a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle.
Specifically, after the model of the accident vehicle is acquired in the above manner, the vehicle photo corresponding to the model of the accident vehicle may be acquired from the network side according to the model, or the corresponding vehicle photo may be selected from photos previously stored by the user in the database according to the model. The photograph of the vehicle according to the present embodiment is a normal photograph of the vehicle of the model, and the normal photograph and the damaged photograph are compared with each other.
Step 103: and determining the vehicle damage part of the accident vehicle according to the vehicle damage picture.
Specifically, the car damage photo specifically includes: close-up photos of the car damage part of the accident car and panoramic photos containing the car damage part of the accident car; determining the vehicle damage part of the accident vehicle according to the vehicle damage picture, which specifically comprises the following steps: and recognizing the vehicle damage part of the accident vehicle in the panoramic picture. The panoramic photo comprises the vehicle damage part and the overall appearance of the vehicle, and the vehicle damage part of the accident vehicle is determined by identifying each part in the panoramic photo. Of course, the names of the various parts of the vehicle defined in advance and the corresponding pictures can be stored in the database, and the pictures can be positioned in the panoramic photo, so that the damaged part of the accident vehicle can be quickly determined.
Step 104: and acquiring a first characteristic parameter of the car damage picture and a second characteristic parameter of the car damage picture. Step 105: and determining the vehicle damage type of the accident vehicle according to the first characteristic parameter and the second characteristic parameter.
Specifically, the first characteristic parameters at least include: the shape and the color of the car damage part, and the second characteristic parameters at least comprise: the shape and color of the corresponding part in the vehicle picture. Obtaining a first characteristic parameter of the car damage photo, specifically: a first feature parameter of the close-up photograph is acquired. After the vehicle damage part of the accident vehicle is identified, the shape and the color of the vehicle damage part are obtained according to the close-up picture of the vehicle damage part, and the shape and the color of the part corresponding to the vehicle damage part in the vehicle picture are obtained according to the obtained vehicle picture. And then determining the vehicle damage type of the accident vehicle according to the first characteristic parameter and the second characteristic parameter. For example: the color of the vehicle in the normal vehicle picture is black, if the color of the damaged part is not black, the damage type of the accident vehicle can be judged to be the scratch by comparing the color of the damaged part with the color of the normal vehicle. For another example: the three-dimensional outline of the damaged part can be seen through the picture shot by the three-dimensional camera, and the three-dimensional outline of the damaged part is compared with the three-dimensional outline of the corresponding part of the picture of the normal vehicle, so that if the two outlines are different, the accident type of the accident vehicle can be judged to be collision. Furthermore, the first characteristic parameter may further include: the area of each color of the car damage part and the second characteristic parameter can further comprise: the area of each color of the corresponding portion in the vehicle photograph. For example, when the damaged portion is a window, if the window is damaged, the color of the damaged portion is darker than that of the intact portion, and therefore, whether the damaged portion is damaged or not can be determined according to the characteristic parameter. They are not illustrated in any way here.
Step 106: and determining the amount of money to be reimbursed of the accident vehicle according to the vehicle loss information of the accident vehicle and the preset corresponding relationship between the vehicle loss information and the amount of money to be reimbursed. Wherein, the car of accident vehicle decreases information and includes at least: the type, the damage part and the damage type of the accident vehicle.
Specifically, the data is preset with a corresponding relationship between the vehicle damage information and the amount to be compensated. The same car damage type appears in different car damage positions, the amount of money required for repairing the car damage type is different, and the amount of money required for repairing the car damage type and the car damage positions are different. As shown in table 1, taking a vehicle model as an example, one vehicle model corresponds to a plurality of loss portions, each loss portion corresponds to a plurality of loss types, and the loss types correspond to specific amounts to be compensated.
TABLE 1
In this embodiment, the amount to be reimbursed may be a specific value or a rough range, and is set according to the average maintenance price at some maintenance points. And according to the vehicle damage information obtained in the step, determining the amount to be compensated of the accident vehicle according to the corresponding relation.
It is worth mentioning that after determining the amount to be reimbursed for the accident vehicle, similar accidents and the final amount to be reimbursed may be recommended to the user for the user's reference. The system evaluates the uploaded pictures through picture comparison, and determines the approximate price range of the maintenance vehicle after evaluating the vehicle damage. Then, a damaged picture uploaded by some car owners and the price and detail of the picture needing to be repaired are provided for the customer to be referred. When the customer finally agrees to the price and the rating is made, the system logs the price and the pictures to gather materials for the owner's questions later.
Further, before acquiring the car damage picture of the accident vehicle, the method further comprises the following steps: sending out prompt information for prompting a user to correctly shoot the car damage picture, wherein the prompt information at least comprises: when the panoramic photo is shot, the damaged part of the car needs to be framed, the correct angle for shooting the panoramic photo and the correct angle for shooting the close-up photo. Before the car damage photo of the accident vehicle is obtained, the user is prompted to shoot the panoramic photo containing the car damage part at any angle, the user is prompted to shoot the close-up photo at any angle, the user can be prompted to frame the car damage part after the complete scene photo is shot, and the car damage recognition is accurate. And the user is guided to shoot the correct car damage picture, so that operation guidance is provided for the user, and the user experience is improved.
Compared with the prior art, the method and the system have the advantages that the car damage picture of the accident car and the model of the accident car are obtained; acquiring a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle; determining the vehicle damage part and the vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture; determining the amount of money to be reimbursed of the accident vehicle according to the vehicle damage information of the accident vehicle and the preset corresponding relationship between the vehicle damage information and the amount of money to be reimbursed, wherein the vehicle damage information of the accident vehicle at least comprises the following steps: the type, the damage part and the damage type of the accident vehicle. According to the car damage photo and the car photo, the car damage position and the car damage type are automatically determined, car damage information is provided for the follow-up automatic determination of the amount of money to be reimbursed, according to the obtained car damage information and the preset corresponding relation, the amount of money to be reimbursed of the accident car is automatically determined, a small accident does not need to be helped by a professional, car damage is automatically recognized, the amount of money to be reimbursed is confirmed, the method is convenient and fast, simultaneously, an indemnification basis is provided for a car driving novice, the probability of cheating is reduced, and user experience is improved.
A second embodiment of the present invention relates to a vehicle damage recognition method. The second embodiment is an improvement on the first embodiment, and the main improvement lies in that: after determining the amount to be reimbursed for the accident vehicle, the method further comprises: judging whether the amount to be compensated is larger than a preset threshold value or not; when the amount to be compensated is judged to be larger than the preset threshold value, sending out prompt information for advising the user to walk insurance maintenance approaches; and when the amount to be compensated is judged not to be larger than the preset threshold value, sending out prompt information for recommending the user to solve privately. Different processing schemes are suggested for the user according to different determined amounts to be compensated, so that the user experience is improved.
A specific flowchart of the vehicle damage identification method according to the present embodiment is shown in fig. 2, and specifically includes:
step 201: and acquiring a car damage picture of the accident vehicle and the model of the accident vehicle.
Step 202: and obtaining a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle.
Step 203: and determining the vehicle damage part of the accident vehicle according to the vehicle damage picture.
Step 204: and acquiring a first characteristic parameter of the car damage picture and a second characteristic parameter of the car damage picture.
Step 205: and determining the vehicle damage type of the accident vehicle according to the first characteristic parameter and the second characteristic parameter.
Step 206: and determining the amount of money to be reimbursed of the accident vehicle according to the vehicle loss information of the accident vehicle and the preset corresponding relationship between the vehicle loss information and the amount of money to be reimbursed.
The steps 201 to 206 are substantially the same as the steps 101 to 106 in the first embodiment, and are not described again.
Step 207: and judging whether the amount to be compensated is larger than a preset threshold value or not. If yes, go to step 208; when the judgment is no, the process proceeds to step 209.
Step 208: and sending out prompt information for recommending the user to go an insurance maintenance way. Step 209: and sending out prompt information for advising the user to solve privately.
Specifically, after the amount to be compensated of the accident vehicle is determined, it is determined whether the amount to be compensated is greater than a preset threshold, wherein the preset threshold may be set to 1000 yuan, when the amount to be compensated is greater than 1000 yuan, it may be determined that the accident occurred in the accident vehicle is not small, the solution is not well solved under private, and at this time, a prompt message advising the user to take an insurance maintenance route is displayed on the intelligent terminal or the display device. When the amount to be compensated is not more than 1000 yuan, the accident of the accident vehicle can be judged to be not large, the private resolution is easy, and the user is recommended to perform the private resolution. Can provide better suggestions for a new driver of driving the automobile, and simultaneously, the accident treatment is more convenient and quicker.
In addition, after determining the amount to be compensated for the accident vehicle, the method further comprises the following steps: and providing information of maintenance points in a preset range of the accident vehicle for a user to make an appointment for maintenance. Specifically, after the amount of money to be paid of the accident vehicle is determined, information of maintenance points within a preset range of the accident vehicle, including the distance between the maintenance points, the internal environment condition and the maintenance price, can be provided for the user, and the user can select a satisfactory maintenance point according to the information of the maintenance points to make an online reservation. When the online reservation is carried out, the mobile phone end can provide an output list, which damage types exist, which items need to be maintained, how much money of each item and the like, the output list can be sent to a maintenance point needing the reservation in a list form, a reserved maintenance time period can be provided, and the time of a user is saved to a certain extent.
Compared with the prior art, after determining the amount to be compensated for of the accident vehicle, the method further includes: judging whether the amount to be compensated is larger than a preset threshold value or not; when the amount to be compensated is judged to be larger than the preset threshold value, sending out prompt information for advising the user to walk insurance maintenance approaches; and when the amount to be compensated is judged not to be larger than the preset threshold value, sending out prompt information for recommending the user to solve privately. Different processing schemes are suggested for the user according to different determined amounts to be compensated, so that the user experience is improved.
The steps of the above methods are divided for clarity, and the implementation may be combined into one step or split some steps, and the steps are divided into multiple steps, so long as the same logical relationship is included, which are all within the protection scope of the present patent; it is within the scope of the patent to add insignificant modifications to the algorithms or processes or to introduce insignificant design changes to the core design without changing the algorithms or processes.
A third embodiment of the present invention relates to an intelligent terminal, as shown in fig. 3, including at least one processor 301; and a memory 302 communicatively coupled to the at least one processor 301; the memory 302 stores instructions executable by the at least one processor 301, and the instructions are executed by the at least one processor 301, so that the at least one processor 301 can execute any of the above-mentioned car damage identification methods.
Where the memory 302 and the processor 301 are coupled in a bus, the bus may comprise any number of interconnected buses and bridges, the buses coupling one or more of the various circuits of the processor 301 and the memory 302. The bus may also connect various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor 301 is transmitted over a wireless medium through an antenna, which further receives the data and transmits the data to the processor 301.
The processor 301 is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory 302 may be used to store data used by processor 301 in performing operations.
A fourth embodiment of the present invention relates to a computer-readable storage medium storing a computer program. The computer program realizes the above-described method embodiments when executed by a processor.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific examples for carrying out the invention, and that various changes in form and details may be made therein without departing from the spirit and scope of the invention in practice.
Claims (10)
1. A vehicle damage identification method is characterized by comprising the following steps:
acquiring a vehicle damage picture of an accident vehicle and the model of the accident vehicle;
acquiring a vehicle photo corresponding to the type of the accident vehicle according to the type of the accident vehicle;
determining a vehicle damage part and a vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture;
determining the amount of money to be reimbursed of the accident vehicle according to the vehicle damage information of the accident vehicle and the preset corresponding relationship between the vehicle damage information and the amount of money to be reimbursed, wherein the vehicle damage information of the accident vehicle at least comprises the following steps: the type of the accident vehicle, the vehicle damage part and the vehicle damage type.
2. The vehicle damage identification method according to claim 1, wherein the step of obtaining the vehicle damage picture of the accident vehicle comprises:
and acquiring the car damage picture of the accident vehicle through an infrared camera or a three-dimensional camera.
3. The vehicle damage identification method according to claim 1, wherein the determining of the vehicle damage part and the vehicle damage type of the accident vehicle according to the vehicle damage picture and the vehicle picture specifically comprises:
determining a vehicle damage part of the accident vehicle according to the vehicle damage picture;
acquiring a first characteristic parameter of the vehicle loss photo and a second characteristic parameter of the vehicle photo, wherein the first characteristic parameter at least comprises: the shape and the color of the car damage part, the second characteristic parameters at least comprise: the shape and color of the corresponding part in the vehicle photo;
and determining the vehicle damage type of the accident vehicle according to the first characteristic parameter and the second characteristic parameter.
4. The vehicle damage identification method according to claim 3, wherein the vehicle damage picture specifically comprises: a close-up photograph of the damaged portion of the accident vehicle and a panoramic photograph containing the damaged portion of the accident vehicle;
the vehicle damage part of the accident vehicle is determined according to the vehicle damage picture, and the method specifically comprises the following steps: identifying a damaged part of the accident vehicle in the panoramic photo;
the method for acquiring the first characteristic parameter of the car damage photo specifically comprises the following steps: a first feature parameter of the close-up photograph is acquired.
5. The vehicle damage identification method according to claim 1, further comprising, after the determining the amount to be reimbursed for the accident vehicle:
judging whether the amount to be compensated is larger than a preset threshold value or not;
when the amount to be compensated is judged to be larger than the preset threshold value, sending out prompt information for advising the user to take insurance and maintenance approaches;
and when the amount to be compensated is judged not to be larger than the preset threshold value, sending out prompt information for advising the user to solve privately.
6. The vehicle damage identification method according to claim 1, wherein after determining the amount to be compensated for the accident vehicle, further comprising:
and providing information of a maintenance point within the preset range of the accident vehicle for the user to reserve maintenance.
7. The vehicle damage recognition method according to claim 1, wherein the model of the accident vehicle is obtained by:
acquiring the model of the accident vehicle manually input by a user;
or acquiring a head photo or a tail photo of the accident vehicle, and determining the type of the accident vehicle according to the head photo or the tail photo.
8. The vehicle damage identification method according to claim 3, further comprising, before the obtaining the picture of the vehicle damage of the accident vehicle:
sending prompt information for prompting a user to correctly shoot the car damage picture, wherein the prompt information at least comprises: when the panoramic photo is shot, a damaged part needs to be framed, the correct angle for shooting the panoramic photo and the correct angle for shooting the close-up photo.
9. An intelligent terminal, comprising:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of identifying a vehicle damage according to any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the vehicle damage identification method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810292585.7A CN108596047A (en) | 2018-03-30 | 2018-03-30 | Vehicle damages recognition methods, intelligent terminal and computer readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810292585.7A CN108596047A (en) | 2018-03-30 | 2018-03-30 | Vehicle damages recognition methods, intelligent terminal and computer readable storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108596047A true CN108596047A (en) | 2018-09-28 |
Family
ID=63624352
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810292585.7A Pending CN108596047A (en) | 2018-03-30 | 2018-03-30 | Vehicle damages recognition methods, intelligent terminal and computer readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108596047A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109344819A (en) * | 2018-12-13 | 2019-02-15 | 深源恒际科技有限公司 | Vehicle damage recognition methods based on deep learning |
| CN109886816A (en) * | 2018-12-04 | 2019-06-14 | 平潭海创智汇科技有限公司 | The control method of carwash scratch danger system |
| CN109886815A (en) * | 2018-12-04 | 2019-06-14 | 平潭海创智汇科技有限公司 | The control method of carwash scratch danger system |
| CN110569701A (en) * | 2018-12-29 | 2019-12-13 | 阿里巴巴集团控股有限公司 | computer-implemented vehicle damage assessment method and device |
| WO2020108144A1 (en) * | 2018-11-30 | 2020-06-04 | 阿里巴巴集团控股有限公司 | Vehicle loss assessment method, device, and system employing vehicle component-loss data |
| CN112418789A (en) * | 2020-11-18 | 2021-02-26 | 德联易控科技(北京)有限公司 | Claims evaluation processing method and device, nonvolatile storage medium and electronic equipment |
| CN112712498A (en) * | 2020-12-25 | 2021-04-27 | 北京百度网讯科技有限公司 | Vehicle damage assessment method and device executed by mobile terminal, mobile terminal and medium |
| CN115222546A (en) * | 2022-07-19 | 2022-10-21 | 武汉中潜咨询有限责任公司 | Insurance business intelligent analysis management system based on big data |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102819880A (en) * | 2012-08-07 | 2012-12-12 | 广东威创视讯科技股份有限公司 | System and method for restoring road accident images all around |
| US8913823B2 (en) * | 2012-10-04 | 2014-12-16 | East West Bank | Image processing method for removing moving object and electronic device |
| CN105488576A (en) * | 2015-12-03 | 2016-04-13 | 小米科技有限责任公司 | Method and apparatus for determining vehicle maintenance and repair expense |
| CN105608533A (en) * | 2015-12-18 | 2016-05-25 | 周桂英 | Method for intelligently distributing stations in vehicle repair plants |
| CN105608428A (en) * | 2015-12-18 | 2016-05-25 | 周桂英 | Method for intelligently identifying automobile appearance damages in repair plants |
| CN105620433A (en) * | 2015-12-18 | 2016-06-01 | 周桂英 | Intelligent vehicle repairing feedback system for vehicle repair plant |
| CN106021548A (en) * | 2016-05-27 | 2016-10-12 | 大连楼兰科技股份有限公司 | Remote damage assessment method and system based on distributed artificial intelligent image recognition |
| CN106780048A (en) * | 2016-11-28 | 2017-05-31 | 中国平安财产保险股份有限公司 | A kind of self-service Claims Resolution method of intelligent vehicle insurance, self-service Claims Resolution apparatus and system |
| CN107092922A (en) * | 2017-03-13 | 2017-08-25 | 平安科技（深圳）有限公司 | Car damages recognition methods and server |
| CN107563893A (en) * | 2017-08-31 | 2018-01-09 | 济南浪潮高新科技投资发展有限公司 | A kind of vehicle insurance Claims Resolution method, client, server and system |
| CN107730485A (en) * | 2017-08-03 | 2018-02-23 | 上海壹账通金融科技有限公司 | Car damage identification method, electronic equipment and computer-readable recording medium |
-
2018
- 2018-03-30 CN CN201810292585.7A patent/CN108596047A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102819880A (en) * | 2012-08-07 | 2012-12-12 | 广东威创视讯科技股份有限公司 | System and method for restoring road accident images all around |
| US8913823B2 (en) * | 2012-10-04 | 2014-12-16 | East West Bank | Image processing method for removing moving object and electronic device |
| CN105488576A (en) * | 2015-12-03 | 2016-04-13 | 小米科技有限责任公司 | Method and apparatus for determining vehicle maintenance and repair expense |
| CN105608533A (en) * | 2015-12-18 | 2016-05-25 | 周桂英 | Method for intelligently distributing stations in vehicle repair plants |
| CN105608428A (en) * | 2015-12-18 | 2016-05-25 | 周桂英 | Method for intelligently identifying automobile appearance damages in repair plants |
| CN105620433A (en) * | 2015-12-18 | 2016-06-01 | 周桂英 | Intelligent vehicle repairing feedback system for vehicle repair plant |
| CN106021548A (en) * | 2016-05-27 | 2016-10-12 | 大连楼兰科技股份有限公司 | Remote damage assessment method and system based on distributed artificial intelligent image recognition |
| CN106780048A (en) * | 2016-11-28 | 2017-05-31 | 中国平安财产保险股份有限公司 | A kind of self-service Claims Resolution method of intelligent vehicle insurance, self-service Claims Resolution apparatus and system |
| CN107092922A (en) * | 2017-03-13 | 2017-08-25 | 平安科技（深圳）有限公司 | Car damages recognition methods and server |
| CN107730485A (en) * | 2017-08-03 | 2018-02-23 | 上海壹账通金融科技有限公司 | Car damage identification method, electronic equipment and computer-readable recording medium |
| CN107563893A (en) * | 2017-08-31 | 2018-01-09 | 济南浪潮高新科技投资发展有限公司 | A kind of vehicle insurance Claims Resolution method, client, server and system |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020108144A1 (en) * | 2018-11-30 | 2020-06-04 | 阿里巴巴集团控股有限公司 | Vehicle loss assessment method, device, and system employing vehicle component-loss data |
| TWI790402B (en) * | 2018-11-30 | 2023-01-21 | 開曼群島商創新先進技術有限公司 | Vehicle damage determination method, device and system based on vehicle component damage data |
| CN109886816A (en) * | 2018-12-04 | 2019-06-14 | 平潭海创智汇科技有限公司 | The control method of carwash scratch danger system |
| CN109886815A (en) * | 2018-12-04 | 2019-06-14 | 平潭海创智汇科技有限公司 | The control method of carwash scratch danger system |
| CN109344819A (en) * | 2018-12-13 | 2019-02-15 | 深源恒际科技有限公司 | Vehicle damage recognition methods based on deep learning |
| CN110569701A (en) * | 2018-12-29 | 2019-12-13 | 阿里巴巴集团控股有限公司 | computer-implemented vehicle damage assessment method and device |
| CN110569701B (en) * | 2018-12-29 | 2020-08-07 | 阿里巴巴集团控股有限公司 | Computer-implemented vehicle damage assessment method and device |
| CN112418789A (en) * | 2020-11-18 | 2021-02-26 | 德联易控科技(北京)有限公司 | Claims evaluation processing method and device, nonvolatile storage medium and electronic equipment |
| CN112712498A (en) * | 2020-12-25 | 2021-04-27 | 北京百度网讯科技有限公司 | Vehicle damage assessment method and device executed by mobile terminal, mobile terminal and medium |
| CN115222546A (en) * | 2022-07-19 | 2022-10-21 | 武汉中潜咨询有限责任公司 | Insurance business intelligent analysis management system based on big data |
| CN115222546B (en) * | 2022-07-19 | 2023-12-15 | 北京力众华援技术服务有限公司 | Intelligent analysis management system for insurance business based on big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108596047A (en) | Vehicle damages recognition methods, intelligent terminal and computer readable storage medium | |
| CN110689761B (en) | Automatic parking method | |
| CN111081064B (en) | Automatic parking system and automatic passenger-replacing parking method of vehicle-mounted Ethernet | |
| CN106710291B (en) | Parking space obtaining method and device for parking lot | |
| CN103940620B (en) | Vehicle failure based on image recognition differentiates and the method and system of prompting | |
| KR102125999B1 (en) | Ai calculation device, method and computer program | |
| CN107730485B (en) | Vehicle damage assessment method, electronic device and computer-readable storage medium | |
| CN109215119B (en) | Method and device for establishing three-dimensional model of damaged vehicle | |
| CN106228449A (en) | Vehicle insurance Claims Resolution antifraud method and apparatus | |
| CN111259848A (en) | Vehicle loss assessment method, vehicle loss assessment system, computer equipment and medium | |
| US10937323B2 (en) | System and method for guiding parking location of vehicle | |
| CN110602446A (en) | Garbage recovery reminding method and system and storage medium | |
| CN115829512A (en) | Vehicle-mounted traffic accident processing method and device, terminal equipment and storage medium | |
| CN115688174A (en) | Privacy protection method and device for vehicle data, vehicle and storage medium | |
| CN108986249B (en) | Vehicle remote damage assessment method and system based on panoramic all-around image | |
| WO2021047249A1 (en) | Data prediction method, apparatus and device, and computer-readable storage medium | |
| CN108062520A (en) | A kind of driver identification system and method | |
| US20230334438A1 (en) | Vehicle Damage Assessment and Repair Process | |
| CN115376356B (en) | Parking space management method, system, electronic equipment and nonvolatile storage medium | |
| CN115457427A (en) | Refueling process monitoring method and device, electronic equipment and storage medium | |
| CN110722982B (en) | Overload processing method and device for test driving vehicle, electronic equipment and storage medium | |
| KR102699264B1 (en) | Apparatus and method for providing charging-position aligning for wireless charging vehicle | |
| CN204884183U (en) | Parking area bluetooth WIFI read head and cell -phone APP assist license plate recognition | |
| CN114771506A (en) | Parking track determination method, device, equipment and storage medium | |
| CN111806458B (en) | Unmanned vehicle reporting method and device, unmanned vehicle and storage medium |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20180928 |
|
| WD01 | Invention patent application deemed withdrawn after publication |