JP3808182B2 - Vehicle repair cost estimation system and recording medium storing repair cost estimation program - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a vehicle repair cost estimation system for estimating a repair cost of a repaired vehicle based on repaired vehicle data obtained by photographing the repaired vehicle with a line-of-sight input digital still camera device, and a recording medium storing a repair cost estimation program.
[0002]
[Prior art]
In recent years, in the estimation of an accident vehicle, a repair cost estimation system by computer processing utilizing a repair work index database, a parts database, etc. supplied from a storage medium such as a CD-ROM has been used.
[0003]
For example, when estimating the repair cost of an accident vehicle whose left front portion has been damaged due to a collision with an oncoming vehicle, first, the damaged portion of the accident vehicle and the degree of damage are determined visually.
Then, when finding damaged parts such as the left front fender, front bumper, radiator grill, headlamp, etc. of the accident car, the estimate person manually inputs each damaged part individually into the repair cost estimation system. Instruct repair work (replacement, desorption, sheet metal, inspection) manually.
[0004]
Then, the repair cost estimation system acquires the repair work index corresponding to the instructed input from the database, calculates the repair technology fee from the lever rate (work unit price) entered in the system in advance, and corresponds to the repair location Obtain the required parts and parts price from the parts database and estimate the repair cost.
[0005]
In addition, past accident vehicle maintenance work information is stored in the accident vehicle repair cost estimation system and displayed on the system display screen as reference materials for new estimates, and vehicle illustration images are displayed on the display screen for estimation. A system has also been proposed in which a person designates a damaged part of an accident vehicle on an illustration image.
[0006]
[Problems to be solved by the invention]
With the above-mentioned conventional system, the price of parts required for repair can be obtained instantaneously, so the estimated work time has been greatly reduced compared to the previous manual estimate work. The estimate and the work of the repair work must be determined from scratch. For this reason, the estimation is based on experience and intuition, and is not based on quantitative figures.Therefore, there is a difference in the estimated cost depending on the work experience and level of the estimator or the level of caution during the estimation. It was possible to reduce the reliability of the estimate.
[0007]
In other words, even if the left front of the vehicle is damaged due to a collision with an oncoming vehicle as described above, the structure of the vehicle differs from vehicle to vehicle, and the magnitude of the force at the time of the accident and the input point of the force are Because it is different, it can be said that the damaged part and degree of damage are completely different for each accident vehicle, and it is rare that the amount of deformation etc. is quantitatively grasped by estimation relying on visual judgment, for example, how much is the bonnet It is necessary to replace it due to deformation or damage of the door, how much the door panel installation position is misaligned, what kind of damage can be considered, what kind of repair is necessary, and how much it is recessed The repair location and the content of the repair work were selected based on experience and intuition without determining whether it would be impossible.
[0008]
However, when estimating the repair cost of an accident vehicle, the vehicle skeleton and the damaged part inside the vehicle that cannot be visually confirmed even if they are visually confirmed from the outside for various kinds of damage according to the accident are actually exterior After disassembling the panel, wheels, etc., if the left side member is not bent, the tension rod bracket is deformed / cracked, etc. In order to make a preliminary estimate, it is necessary to rely on experience and intuition to confirm the opposite side (right side) part, parts, etc. that seem to be apparently not damaged by the accident case. There is also the actual situation.
[0009]
Therefore, in the estimation stage, there are many cases where considerably rough repair work items are listed, and after actually repairing the accident vehicle, the work actually performed is input to the repair cost estimation system.
[0010]
Therefore, the object of the present invention is based on such points, and the determination of the damaged part and the repair work contents manually input by experience and intuition is quantified based on the repair vehicle data photographed using the gaze input digital still camera device. The cost of repair can be estimated easily and quantitatively, and the basis of the estimate content is recorded together with the photographed image, and the level of repair cost estimation work is made uniform at a high level and appropriate and transparent. It is an object of the present invention to provide a vehicle repair cost estimation system and a recording medium storing a vehicle repair cost estimation program that enable a prior estimate.
[0011]
Another object of the present invention is to provide a vehicle repair cost estimation system and vehicle repair capable of automatically and accurately calculating a painting fee based on repair vehicle data photographed using a line-of-sight input digital still camera device. The object is to provide a recording medium storing a cost estimation program.
[0012]
[Means for Solving the Problems]
The present invention employs the following means in order to solve the above-described problems.
In other words, the vehicle repair cost estimation system according to the present invention is a vehicle repair cost estimation system that estimates the repair cost of a repaired vehicle using a programmed calculation device.
[0013]
And an image sensor that detects a line-of-sight position on a secondary plane of the image, and the line-of-sight position of a photographer who photographs the repair vehicle based on the line-of-sight position data detected by the image sensor. A line-of-sight input digital still camera device having an image storage unit for storing captured image data as well as detection data, and outputting the damaged portion detection data and the captured image data stored in the image storage unit as repair vehicle data; The vehicle attribute data corresponding to the repaired vehicle is retrieved from the previously stored vehicle attribute data, and the repaired vehicle data is input based on the output of the line-of-sight input digital still camera device. Specify range and amount of deformation or at least one of these, and repair costs And a computing computing device, performs a repair cost estimate based on the vehicle attribute data and the repair vehicle data.
[0014]
Next, the vehicle repair cost estimation system includes an image sensor that detects a line-of-sight position on a secondary plane of an image, and a photographer shooting a repair vehicle based on the line-of-sight position data detected by the image sensor. The line-of-sight position is stored as damaged part detection data of the repaired vehicle, and has an image storage unit for storing captured image data. The damaged part detection data and the captured image data stored in the image storage unit are used as repaired vehicle data. The line-of-sight input digital still camera device to be output and vehicle attribute data corresponding to the repaired vehicle are searched from previously stored vehicle attribute data, and the repaired vehicle data input based on the output of the line-of-sight input digital still camera device is Use repair vehicle damage location, damage range and damage degree or at least one of them Identify, and a computing device for calculating the repair cost of the repair vehicle.
[0015]
And the said calculation apparatus inputs the said repair vehicle data required for the said repair cost calculation, and stores beforehand the non-damaged vehicle image data corresponding to the said repair vehicle as vehicle attribute data, and this non-damaged vehicle image data and Comparing and calculating the repair vehicle data to identify the damage position, damage range and damage degree of the repair vehicle or at least one of them, and estimating the repair cost based on the vehicle attribute data and the repair vehicle data It is.
[0016]
Further, the repair vehicle data includes damaged part detection data based on a plurality of line-of-sight positions, line segments connecting the line-of-sight position data are used as damaged part detection data, and / or line segments connecting the line-of-sight position data are contours. The closed section range to be used can be used as damaged portion detection data.
[0017]
According to the present invention, the image data of the repair vehicle captured from the line-of-sight input digital still camera device is input to the calculation device, and the calculation device receives the vehicle attribute data corresponding to the image data of the repair vehicle from the previously stored vehicle attribute data. Search for.
[0018]
Then, the damage position, damage range and deformation amount of the repair vehicle are determined based on the input image data of the repair vehicle, and the repair cost is estimated using the repair vehicle image data based on the vehicle attribute data. is there.
[0019]
Furthermore, the repair vehicle data and non-damaged vehicle image data are compared and calculated to determine the damage position, damage range and damage level of the repair vehicle. Repair vehicle The repair cost is estimated using image data.
[0020]
Next, the line-of-sight input digital camera device constituting the present invention forms an image of light incident through the lens system on an imaging plate such as a CCD and converts it into an electrical signal, and then stores this information in a memory. It can be output.
[0021]
In addition, it is possible to sense a photographer's line of sight, photograph the line of sight position as a focal point, and store the line of sight position together.
The principle is to irradiate the human eyeball with a weak light beam and direct the reflected light to the image sensor to calculate the angle of the eyeball, that is, the direction of the line of sight. However, it is preferable that the row is increased to provide a focal point of 15 points for 3 rows and 25 points for 5 rows.
[0022]
Therefore, this line-of-sight input digital camera device uses the repaired vehicle image data of the repaired vehicle as well as the repaired vehicle data of the repaired vehicle's line-of-sight position of the photographer shooting the repaired vehicle based on the line of sight position data .
[0023]
In addition, it is preferable that the outer panel panel position data of the line-of-sight position can be stored simultaneously as information data to be added to the line-of-sight position data. For example, the gaze input digital camera device incorporates repair vehicle specification data such as the position of the outer panel and the name of the outer panel into a ROM, and the same button operation or dial operation as when changing the shutter speed, exposure, etc. The outer panel position, the panel name, etc. can be stored.
[0024]
In this way, the names of the damaged positions such as the left front panel and the front bumper are displayed at an arbitrary position in the image (preferably each line-of-sight input position or each in-focus position other than the line-of-sight input position). Rankings such as “No significant breakage, crushing, or extension”, “Spanning the press line”, etc. are made to recognize the position and match the deformation amount of these damaged positions according to the damage form according to the difficulty level determination of the work index It is also possible to discriminate and store them.
[0025]
As a further measure, a transmissive vehicle image screen in which the outer panel position is stored in advance is used, and the sight line position is reflected on the outer panel panel position by collating the sight line position with the transmissive vehicle image screen. In the case where the damage position is the left front panel and the front bumper, it can be configured to recognize the position of the arbitrary line-of-sight position in the image on the left front panel and the front bumper.
[0026]
In addition, it is possible to store the vehicle verification description data such as the owner and the vehicle number in the line-of-sight input digital still camera device, and it is also possible to store it in association with the repair vehicle data.
[0027]
Further, the repair vehicle data output from the line-of-sight digital still camera device and the input to the calculation device can be performed by a communication function or a recording medium such as a memory card, and an appropriate input / output interface is used. it can. Conversely, predetermined data can also be input to the line-of-sight input digital still camera device from a computing device, a portable electronic terminal device, or the like by the same method.
[0028]
If the line-of-sight digital still camera device has a communication function, it is also possible to transfer the stored contents using a communication medium such as a mobile phone or a PHS. It is also possible to transfer data by communication.
[0029]
Next, the calculation device for calculating the repair cost is connected or built in an auxiliary storage device for reading these data from a recording medium in which vehicle attribute data is stored in advance. This recording medium uses a CD-ROM, MO, floppy disk or the like.
[0030]
The pre-stored vehicle attribute data includes classification data of almost all passenger vehicles currently running in Japan, model data, vehicle specification data such as vehicle weight, and vehicle registration data such as registered land transportation offices, Desorption / replacement work index, desorption / replacement work index, outer plate modification work index, and outer plate modification work data, which are the basis for calculating vehicle parts price and labor required for replacement or modification of this part, Stores each work index data group such as plate skeleton modification work index, inner plate skeleton modification work data, painting index and painting work data, and can be replaced, removed, modified, adjusted, etc. according to the damaged part and damage degree of the vehicle Stores correspondence data with necessary parts and other various data necessary for repair estimation.
[0031]
The stored data includes repair vehicle data stored in the line-of-sight input digital still camera device.
Furthermore, past repair vehicle data, past repair vehicle damage data grasped from this data, parts data used in the past repair vehicle, and vehicle image data for searching for the past damage position, etc. Can be stored.
[0032]
Next, the display device, such as a CRT or a liquid crystal panel, displays an image, and may have a touch sensor on the surface. As the input device, a keyboard, a pointing device such as a mouse, a light pen, or the like can be used.
[0033]
Next, the calculation device performs repair cost estimation processing using repair vehicle data input on the basis of vehicle attribute data, and includes a central processing unit (hereinafter referred to as a CPU), a hard disk, a RAM, a ROM, and the like. Main memory device (hereinafter referred to as memory).
[0034]
Then, the calculation device analyzes the repair vehicle data displayed on the display device, and uses this as basic data for the repair estimate. This analysis work may be either manual processing or automatic processing using a keyboard or mouse, and each data file in a memory storing repair vehicle data stores a number for identifying the corresponding repair vehicle data. The corresponding repair vehicle data can also be stored in the data file created for each part.
[0035]
In addition, the repair vehicle data displayed on the display device and the non-damaged vehicle image data stored in the memory in advance can be compared and calculated to allow detailed analysis of the repair vehicle data input from the line-of-sight digital still camera device. You may comprise as follows. The computing device may have a communication function for transmitting and receiving data to the outside.
[0036]
In the vehicle repair cost estimation system configured as described above, when actually performing repair vehicle estimation work, first, repair vehicle data (including image data) including damaged portion detection data photographed by the line-of-sight input digital still camera device is used. ) To the computing device through the input / output interface.
[0037]
On the other hand, from the memory, a typical vehicle figure of an overall view and a partial view of the vehicle is displayed on the display device. Here, it is automatically determined from the data stored in the line-of-sight input digital still camera device which portion of the repair vehicle data displayed corresponds to the whole view or the partial view. May be. This makes it clear where each image data indicates damage.
[0038]
Similarly, all repair vehicle data (including image data) is analyzed, and basic data regarding damage to the repair target vehicle is calculated from the line-of-sight input position and other information data.
[0039]
When the repair cost is calculated by the calculation device, the repair cost is estimated based on the basic data regarding the damage of the repair target vehicle calculated from the line-of-sight input position and other information data. At this time, the repair contents of the model case and the damage basic data of the repaired vehicle may be collated.
[0040]
The displayed data is printed out as necessary. Display data can also be stored in a server or external memory.
Next, the vehicle repair cost estimation system according to the present invention uses a recording medium storing the following program in order to estimate the repair vehicle repair cost.
[0041]
That is, it has means for retrieving vehicle attribute data corresponding to the repaired vehicle from vehicle attribute data stored in advance, and an image sensor for detecting the position of the line of sight on the secondary plane of the image, and the line of sight detected by this image sensor The line-of-sight position of the photographer shooting the repaired vehicle based on the position data is stored as damaged part data of the repaired vehicle, and has an image storage unit that stores the captured image, and the captured image stored in the image storage unit Input means capable of inputting as repair vehicle data, display means for displaying repair vehicle data relating to the repair vehicle and vehicle attribute data corresponding to the repair vehicle or at least one of them, and the input repair vehicle data Is used to identify the repair vehicle's damage location, extent and extent or at least one of them, Serial is readable recording medium recording a program for executing the means for performing the repair cost estimate of the repair vehicle based on the vehicle attribute data and the inputted the repaired vehicle data.
[0042]
DETAILED DESCRIPTION OF THE INVENTION
Hereinafter, the vehicle repair cost estimation system according to the present embodiment will be specifically described with reference to FIGS.
[0043]
The vehicle repair cost calculation system according to the present embodiment uses a personal computer 1 (hereinafter referred to as a PC) and a line-of-sight input digital still camera device 5 as shown in FIG. The repair cost estimate for the repaired vehicle is made.
[0044]
The vehicle repair cost calculation system includes an auxiliary storage device 3 (CD-ROM, MO, FD, etc.) and an input device 4 (keyboard, OCR, OMR, bar code reader, digitizer, image) connected through the input / output interface 2. Scanner 1), line-of-sight input digital still camera 5, PC 1 main body composed of main storage device 1 b (hard disk, ROM, RAM (hereinafter referred to as “memory”)) and central processing unit 1 a (hereinafter referred to as “CPU”); It is formed by an output device composed of the connected display device 6, printing device 7, communication device 8 and the like. Further, the communication device 8 is connected to a terminal device (not shown) through a communication line.
[0045]
Next, the PC 1 includes a hard disk, a RAM, and a ROM as the memory 1b, and stores a necessary OS in advance.
That is, a program cached in the memory 1b or the auxiliary storage device 3 is started under the control of the OS, and a predetermined task (process) is executed.
[0046]
Then, the CPU 1a constituting the PC 1 main body performs an arithmetic operation 1a, a logical operation, etc. on given data. ₂ And the instruction part 1b to be executed ₁ The control device 1a fetches a command from the memory 1b to the CPU based on the address of the command, decodes the content of the command, and issues a necessary operation instruction to another device ₁ And have.
[0047]
This control device 1a ₁ 1 issues an input control command to the input device or the like as shown in FIG. 1, issues a memory control command to the memory 1b, and issues an output control command to the display device or the like.
[0048]
Then, a command input from the input device 4 or the like is first transferred to the memory 1b, and the memory 1b selects data and an instruction from the given command, and the selected data and instruction are respectively stored in the data portion 1b. ₂ And command part 1b ₁ And the control device 1a of the CPU 1a ₁ Forward to.
[0049]
Next, vehicle graphic data is stored in advance in the memory or CD-ROM, and the vehicle graphic data stores typical figures such as a sedan car and a hard top car. Select the vehicle figure corresponding to the vehicle.
[0050]
The selected vehicle graphic is displayed as an overall view of the vehicle graphic 6a as, for example, three-dimensional graphics, and is displayed on the display device 6 connected to the PC 1 through the input / output interface 2.
[0051]
The vehicle figure 6a displayed on the display device 6 may be an image of a real vehicle. Further, the vehicle figure 6a data further stores the vehicle figure 6a for each vehicle type (car A, car B, car C,...) In detail, and displays a figure suitable for each car type on the display device 8. You may be made to do.
[0052]
By the way, the CD-ROM mounted inside the CD-ROM drive includes classification data, model data, vehicle specification data such as vehicle weight, automobiles such as registered land transportation offices, etc. for almost all passenger vehicles currently running in Japan. Including registration-related data, the detachment / replacement work index and detachment / replacement work data, the outer plate modification work index, and the outer plate, which are the basis for calculating the parts price of the vehicle and the labor required to replace or modify this part Stores each work index data group such as correction work data, inner plate skeleton correction work index and inner plate skeleton correction work data, painting index and painting work data, and replacement, desorption, etc. according to the damaged part and degree of damage of the vehicle, Corresponding data with parts that need correction, adjustment, etc., and other various data necessary for repair estimation are stored.
[0053]
These data groups are stored in the data portion 1b of the PC 1 from the CD-ROM through the input / output interface. ₂ Stored in
Next, the line-of-sight input digital still camera device 5 for photographing the repair vehicle is configured to form an image of light incident from the lens system 42 on the CCD 43 as shown in FIG. After being compressed by the (micro prossing unit) 44, it is stored in the image storage unit 40 which also serves as a video recording. Then, the stored image is transferred to the PC 1 through the interface 45.
[0054]
On the other hand, the line-of-sight input digital still camera apparatus 5 is provided with an optical finder 46, and two half mirrors 47 and 49 are arranged in the optical finder 46.
[0055]
The half mirror 47 reflects the photographer's line of sight and forms an image on the image sensor 41, and the half mirror 48 irradiates the photographer's eye with the light beam of the light emitting diode 49.
[0056]
The output of the image sensor 41 is processed by the MPU 44, and the image sensor 41 covers a plane composed of pixels such as L1 and L2 as shown in FIG. 3, and can correspond to the line-of-sight position.
[0057]
Next, the light emitted from the light emitting diode 49 is refracted by the half mirror 48 and reaches the eyeball. Then, the light reflected by the eyeball is reflected by the half mirror 47 and enters the image sensor 41. Here, since the reflected light changes depending on the angle of the eyeball, that is, the line of sight, the MPU 44 calculates where the photographer puts the line of sight from this information.
[0058]
Here, as shown in FIG. 4, when there is a linear scratch 6b on the left front door of the vehicle, when the shutter of the line-of-sight input digital still camera device 5 is first aligned with the scratch starting point M1, the line of sight is displayed. The portion where is placed is designated and stored in the image storage unit.
[0059]
Next, when the shutter of the line-of-sight input digital still camera device 5 in which the line-of-sight position is aligned with the wound end point M2, the portion where the line of sight is placed is designated.
The line-of-sight positions (hereinafter referred to as in-focus points) M1 and M2 thus specified are temporarily stored in the image storage unit, and the stored images are transferred to the PC 1 through the interface 45. Here, the line-of-sight input digital still camera device 5 detects the distance from the captured focal point M1 to the line-of-sight input digital still camera device 5, and the distance from the focal point M2 to the line-of-sight input digital still camera device 5 Is detected.
[0060]
Then, the PC 1 calculates a distance (here, a linear distance) from the focal point M1 to the focal point M2 based on the inputted focal point M1 and the distance from the focal point M2 to the line-of-sight input digital still camera device 5. To do. That is, the linear distance is calculated by performing triangulation based on the distance from the focal point M1 and the focal point M2 to the line-of-sight input digital still camera device 5. It should be noted that the principle of triangulation starts with the selection of several points such that the line of sight connecting each point forms one triangle or several continuous triangles. Each triangle shares at least one side with each adjacent triangle. The first side, i.e., the baseline, is then measured in the same way as all angles, and all remaining side lengths are calculated by sequentially using the sine law. In addition, since the direction of the side is sequentially calculated, the relative positions of all the points are determined.
[0061]
Next, the line-of-sight input digital still camera device 5 incorporates repair vehicle specification data such as the position of the outer panel and the name of the outer panel into a ROM, and incorporates the shutter speed and exposure into the line-of-sight digital still camera device 5. It is also possible to store the outer panel position, the panel name, etc. by the same button operation or dial operation as in the case of changing.
[0062]
In this way, the names of the damaged positions such as the left front panel and the front bumper are displayed at an arbitrary position in the image (preferably each line-of-sight input position or each in-focus position other than the line-of-sight input position). Rankings such as “No significant breakage, crushing, or extension”, “Spanning the press line”, etc. are made to recognize the position and match the deformation amount of these damaged positions according to the damage form according to the difficulty level determination of the work index It is also possible to discriminate and store them.
[0063]
By designating the damaged part and the shape of the damage in this way and inputting them into the PC 1, the PC 1 causes the display device 6 to display image data including the left front door that is the damaged part.
[0064]
Then, the PC 1 specifies a substantially linear flaw along with the position of damage based on the designated focal point M1 and focal point M2. That is, the image data of the repair vehicle is drawn on a large number of pixels, and the address of the pixel corresponding to the line-of-sight position (focus point M1, focus point M2) is searched, and the damage position is identified based on the pixel address. At the same time, the shape and length of the flaw is analyzed by connecting these line-of-sight positions.
[0065]
Next, in order to specify a slight degree of dent damage, the line of sight is moved to the positions M3, M4, and M5 as shown in FIG. The section surrounded by the focal points M3, M4, and M5 is analyzed, and the length of the line segment that connects the focal points M3, M4, and M5 is determined. Then, when the length of the line segment is calculated, the triangular area, that is, the damage range can be calculated based on these lengths.
[0066]
The degree of damage can also be determined based on the distance from the focal points M3, M4, and M5 to the line-of-sight input digital still camera device 5. Here, when determining the extent of the substantially triangular scratch, that is, the amount of deformation, for example, a recess is formed substantially at the center of the triangular scratch, and the center is the maximum depth of the recess. Aim the line of sight and release the shutter. Then, the distance from the focal point M3 to M5, which is the outer edge of the wound photographed so far, to the line-of-sight input digital still camera device 5 and the distance from the focal point M6 to the line-of-sight input digital still camera device 5 are indentations. Only the distance from the focal point M6 to the line-of-sight input digital still camera device 5 is increased.
[0067]
Therefore, by comparing the distance from the focal point M3 to M5 to the line-of-sight input digital still camera device 5 and the distance from the focal point M6 to the line-of-sight input digital still camera device 5, the depth of the recess, that is, the deformation amount. Can be analyzed.
[0068]
Further, the line-of-sight digital still camera device 5 here also includes repair vehicle specification data such as the position of the outer panel and the name of the outer panel in a ROM format, and is similar to the case where the shutter speed, exposure, etc. are changed. It is also possible to store the outer panel position, the panel name, etc. by button operation or dial operation.
[0069]
Then, these data are input to the PC 1 through the input / output interface 2, and the PC 1 causes the display device 6 to display image data including the left front door which is a damaged portion.
[0070]
Then, the PC 1 specifies a substantially triangular wound along with the position of the damage based on the designated focal points M3 to M5. Then, the deformation amount is specified based on the focal points M3 to M5 and the focal point M6.
[0071]
That is, the model image data of the vehicle is drawn on a large number of pixels, the addresses of the pixels corresponding to the viewpoints M3 to M5 are searched, and the damage position is specified based on the addresses of the pixels. , The area surrounded by the flaw shape, the viewpoint M1 to the viewpoint M3, and the degree of the dent are specified.
[0072]
By the way, the damage position, damage range, and deformation amount of the repair vehicle described above are limited to damage that can be quantitatively grasped by the line-of-sight input digital still camera device 5.
[0073]
That is, the line-of-sight digital still camera device 5 can quantitatively specify the damage of the repaired vehicle based on the damage position designated by the line-of-sight digital still camera device 5 or the address of the pixel corresponding to the focal point. Grasping the position quantitatively, and then connecting the focal points shown on the image data of the repaired vehicle imported to PC1, and calculating the length of the line segment between these focal points From this length, it is possible to quantitatively grasp the area that is the damage range, calculate the distance from the line-of-sight input digital still camera device 5 to each focal point, and quantitatively determine the deformation amount from the length of these distances. It is to grasp.
[0074]
Here, for example, whether or not discrimination is possible is stored in the PC 1 in advance as a threshold value, and the repair vehicle data from the line-of-sight input digital still camera device 5 is analyzed. When the value exceeds the value and it is determined that the amount of deformation cannot be determined quantitatively, the degree of damage is specified by comparing and calculating repair vehicle data and non-damaged vehicle image data described below.
[0075]
That is, as shown in FIG. 6, when a damaged portion extends over a plurality of portions and the amount of deformation is complicated and the degree of damage is large, the line of sight is aligned with each damaged portion to obtain a focal point for each damaged portion.
[0076]
Here, the focal point is the focal point M7 on the left front panel, the focal point M8 on the left front bumper, the focal point M9 on the left headlight, and the focal point M10 on the left front fender.
[0077]
A plurality of repair vehicle data (damaged part detection data, photographed image data) of the repaired vehicle photographed in this manner is input to the PC 1 and compared with the non-damaged vehicle image data, so that the damage position of the repaired vehicle, Analysis of damage range and damage level is performed.
[0078]
Here, in the analysis of the damage position, the damage range, and the damage degree, the binarization process is performed on the repair vehicle data that is first photographed and input to the PC 1. This binarization process is to obtain a black and white (1, 0) binary image from a multi-tone image. A certain threshold is set for the multi-tone image, and the density value of each pixel is larger than this threshold. If it is smaller, the value of each pixel is converted to 1 or 0. As these methods, a p-tile method and a mode method are known.
[0079]
Next, the contour line is traced from the binarized repair vehicle image data. In this contour line tracking process, image data is first raster-scanned to find a point having a pixel value of 1 (a point having a contour line shape) without a tracked mark.
[0080]
And the corresponding point P ₀ Is found, the pixel values in the vicinity of 4 (4 connected) or 8 (8 connected) of the point are examined clockwise (or counterclockwise). Next, the first pixel of value 1 found is set to the next contour point P ₁ Continue tracking as.
[0081]
The point P thus obtained ₁ Search for a point of value 1 in the vicinity of 4 (or 8) ₀ Except).
Next, point P ₁ A point with value 1 in the vicinity of 4 (or 8) ₂ In the same manner, P _Three , P _Four Go for. Here, after N traces, P _N = P ₀ When it comes to, the tracking process ends.
[0082]
And each P _i In the case of a closed loop, the process returns to the original place so that the process is terminated. In the case where the tracking paths intersect, a smooth direction or a direction in which there is a unity is selected to proceed.
[0083]
Next, when the analysis of the contour is completed, smoothing processing and feature extraction can be performed. By performing the smoothing process, it is possible to obtain a sharpening effect in which the edge where the density value changes is enhanced and the image becomes clearer. Further, by extracting features, it is possible to extract feature points such as bent points and discontinuous points, extract feature lines such as thickness, position, and orientation, and analyze feature surfaces such as refractive index, curvature, and surface roughness.
[0084]
Then, comparison with non-damaged vehicle image data stored in advance and binarized is performed, and feature points, feature lines, feature surfaces, etc. extracted by feature extraction or the like are compared at any time to analyze the damage range and damage degree.
[0085]
In this way, by comparing the image data of the repaired vehicle and the non-damaged vehicle image data of the normal vehicle, the damaged position (here, the left front panel, the left front bumper, the left headlight, the left front fender) is detected, Furthermore, it is possible to identify the damage range and the degree of damage at the detected damage position.
[0086]
Next, when the identification of the damage position, the damage range, the deformation amount or the damage degree is completed, the estimation calculation is started. The estimate calculation of the vehicle repair cost is performed by the estimate creator inputting data necessary for repair while viewing the image data of the vehicle displayed on the display device 6.
[0087]
First, image data of a repaired vehicle to be estimated is input to the PC 1 through the input / output interface 2. Next, vehicle type specifying data such as vehicle specification data and automobile registration related data is input from the input device 4.
[0088]
When these data are input, the vehicle attribute data corresponding to the repaired vehicle is searched. Next, the PC 1 specifies the damage position, the damage range, and the deformation amount that can be quantitatively specified from the repair vehicle data input from the line-of-sight input digital still camera device 5, and the damage that cannot be quantitatively specified. The degree of damage is calculated by comparing the repaired vehicle data with the non-damaged vehicle data corresponding to the repaired vehicle data to calculate the damage position, the damage range, and the damage degree.
[0089]
Next, when these identifications are completed, the PC 1 causes the display device 6 to display a list of the contents of all obtained repair vehicle data. Furthermore, the PC 1 displays the image data of the repaired vehicle input from the line-of-sight input digital still camera device 5.
[0090]
Next, the input device 4 selects necessary data from various data of the repaired vehicle displayed on the display screen of the display device 6. Here, when the selected data is detachment / replacement work data for calculating labor required for replacement or correction of parts, the PC 1 retrieves the part price data and detachment / replacement work data, and these detachment / replacement work data. The contents of the replacement work data are displayed as a list on the display device 6.
[0091]
Then, necessary work parts and the like are selected from all the detachment / replacement work data displayed as a list on the display screen of the display device 6 and input from the input device 4. When the value of the code classification data in the detachment / replacement work data selected in this way is 0, the work index database is searched using the detachment / replacement work code data to obtain work name data and work index data.
When the value of the code classification data in the selected detachment / replacement work data is 1, the parts master database is searched using the detachment / replacement work code data to obtain part name data and part price data.
[0092]
Next, the PC 1 calculates the total work amount from each work index data in the obtained search results. Specifically, the PC 1 calculates each work amount data by multiplying each obtained work index data by a predetermined work unit price (lever rate). Then, the sum total of these pieces of work amount data is calculated to obtain total amount data.
[0093]
Next, the PC 1 causes the output device to print a vehicle repair cost estimate based on the obtained work name data, work amount data, part name data, part amount data, and vehicle repair cost amount data. Further, the contents of the vehicle repair cost estimate are displayed on the display device.
[0094]
Next, an example of a process for creating a repair cost estimate based on an actual display screen will be described. Here, the estimate to be created is a creation process in the case of correcting this scratch with respect to the aforementioned linear scratch on the left front door. The data displayed on the display screen displays not only the repair location but also the cost for replacement.
[0095]
Then, as shown in FIG. 7, a plurality of image data of the repair vehicle photographed by the line-of-sight input digital still camera device 5 is displayed on the display device 6.
Here, when the repair cost estimate calculation of the repair vehicle is performed for the damaged portion (here, the scratch on the left front door) that can be quantified by the line-of-sight input digital still camera device 5, the estimate creator includes the repair vehicle including the left front door. Vehicle image data is selected, and an image to be displayed is selected and input from the input device.
[0096]
Then, as shown in FIG. 8, image data including the estimated damage position selected from the plurality of image data captured by the line-of-sight input digital still camera device 5 is displayed on the display device 6.
[0097]
Here, the displayed content is a damage area of 4 dm ² The extent of damage is 4 dm ² In the following, there is no significant breakage, crushing, or extension, the damage position is a position that does not reach the press line portion or the panel end, and the workability is displayed that the work can be performed with a hammer, dolly, spoon, etc. from the back of the panel. Here, if there is an error in the contents of work position and workability, the contents can be changed by placing the cursor on the position of No and clicking.
[0098]
Next, if there is no error in the damaged area, degree of damage, damaged position, and workability, and there is no need to change them, the specific contents of the cost of repairing the left front door as shown in FIG. Is displayed.
[0099]
The display screen shown in FIG. 9 simultaneously displays the damage range (here, the length of a straight line) quantified by the line-of-sight input digital still camera device 5 together with the display of the image data, and is based on the quantified damage range. The calculated work time and difficulty level are displayed.
[0100]
Here, the work time is specified by storing the correlation between the deformation amount of the damage range and the work time in advance in a memory as a map, and storing the deformation amount obtained from the line-of-sight input digital still camera device 5. Calculate by positioning on top.
[0101]
Next, the work difficulty level is obtained from the line-of-sight input digital still camera device 5 in which a correlation between the deformation amount of the damage range and the difficulty level is stored in advance in a memory as in the case of specifying the work time. The deformation amount is calculated by positioning it on the stored map.
[0102]
Specifically, this linear scratch has a damage range of 4 dm. ² , The area is also 4dm ² The working time is displayed with an index of 1.40 hours and a difficulty level of 1.00.
And the expense concerning correction of a front door is displayed on a display screen. The cost for the modification of the front door is calculated by multiplying the lever rate, which is the work cost per unit time, by an index of 1.40 corresponding to the difficulty of the work, and the technical fee is 9,800 yen. Multiply the rate by the index of 0.30 and the technical fee is 2,100 yen. For painting, set the lever rate to 7,000 yen, multiply by the index of 2.60 and the technical fee is 18,200 yen. The fee is 1,760 yen, and the total cost for the modification of the front door is 31,860 yen.
[0103]
Next, the operation principle of the PC 1 will be described based on the flowchart shown in FIG.
First, various data relating to a repaired vehicle such as vehicle specification data for specifying a vehicle type of the repaired vehicle and vehicle registration related data are input by the input device 4 and transferred to the PC 1 through the input / output interface 2 (step 100). Then, repair vehicle data including a plurality of damaged portion detection data and photographed image data of the repair vehicle photographed by the line-of-sight input digital still camera device 5 is input to the PC 1 through the input / output interface 2 (step 101, step 102).
[0104]
Next, the value obtained from the analysis result of the input repair vehicle data is compared with a preset threshold value, and it is determined whether or not the value is within the set threshold value range. (Step 103).
[0105]
Here, when it is determined that it is within the set threshold range, the damage position, the damage range, and the deformation amount are specified from the damaged portion detection data and the captured image data captured by the line-of-sight input digital still camera device 5 ( Step 104).
[0106]
Next, various work data such as detachment / replacement work data and skin correction work data displayed on the display device 6 are input (step 105). Then, the PC 1 performs estimation calculation based on these data (step 106). In step 106 and subsequent steps, necessary parts are collated from the deformation amount at each damage position, and a list of parts necessary for repair is obtained. Then, each price of the parts group and each labor cost are calculated. This result is displayed on the display device 6.
[0107]
The estimation result obtained in this way can be printed out on a paper whose format has been determined in advance by the printing device 7 (step 107).
Next, returning to step 103, when it is determined that the value is outside the set threshold range, the comparison operation between the repair vehicle data photographed by the line-of-sight input digital still camera device 5 and the non-damaged vehicle image data is performed on the image. The correction is performed while correcting the data (steps 108 and 109), and the damage position, damage range and damage degree are specified based on the comparison calculation result (step 110).
[0108]
Next, various work data such as detachment / replacement work data and skin correction work data displayed on the display device 6 are input (step 111). Then, the PC 1 performs an estimate calculation based on these data (step 112). In step 112 and subsequent steps, necessary parts are collated from the amount of deformation at each damage position, and a list of parts necessary for repair is obtained. Then, each price of the parts group and each labor cost are calculated. This result is displayed on the display device 6.
[0109]
The estimation result obtained in this way can be printed out on a paper whose format has been determined in advance by the printing device 7. (Step 113)
As described above, it is possible to take an image with the line-of-sight input digital still camera device 5 while observing the damaged portion of the repaired vehicle, and specify the damage position, the damage range, the deformation amount, or the damage degree by inputting the image into the system. Therefore, it is possible to quickly calculate the parts, repair time, and cost required for the subsequent repair.
[0110]
【The invention's effect】
According to the present invention, when the image of a plurality of repaired vehicles is captured by the line-of-sight input digital still camera device, and the repaired vehicle data is input to the calculation device, the calculation device has damage that can be quantified by the line-of-sight input. The damage position, damage range and deformation amount are identified based on the repair vehicle data, and the repair cost estimate of the repair vehicle is based on the various stored and selected work data and the specified damage position, damage range and deformation amount. I do. Therefore, the damage position, the damage range, and the deformation amount can be visually confirmed so far, and the trouble of manually inputting these can be saved, and further, the visual error can be prevented.
[0111]
In addition, the repair cost can be estimated simply and quantitatively, and the basis of the estimated content can be recorded together with the photographed image, so that the repair cost estimation work can be made uniform and appropriate and transparent sheet metal work can be estimated in advance.
[0112]
Furthermore, the estimation process can be performed efficiently, and the time taken to create the estimate can be greatly reduced.
Next, in the case of damage that cannot be quantified by line-of-sight input, the repair vehicle data and non-damaged vehicle image data are compared and identified, and the damage position, damage range, and damage degree are specified, and stored and selected in advance. The repair cost of the repaired vehicle is estimated based on the various work data thus specified and the specified damage position, damage range, and deformation amount. Therefore, here again, it is possible to visually confirm the damage position, damage range, and damage degree required for the conventional estimation calculation, and to save the trouble of manually inputting these, and to prevent visual errors.
[0113]
Furthermore, since the estimate prepared using the repair cost estimation system according to the present invention can clearly indicate the damage position and the like together with specific numerical values, a clear and transparent estimate is presented to the user. be able to.
[Brief description of the drawings]
FIG. 1 is a block diagram of a vehicle repair cost estimation system according to an embodiment of the present invention.
FIG. 2 is a block diagram of a line-of-sight digital still camera according to the present embodiment.
FIG. 3 is a front view showing pixels of an image sensor portion of the line-of-sight input digital still camera according to the present embodiment.
FIG. 4 is a photographed image diagram of the vehicle repair cost estimation system according to the present embodiment.
FIG. 5 is a photographed image diagram of the vehicle repair cost estimation system according to the present embodiment.
FIG. 6 is a photographed image diagram of the vehicle repair cost estimation system according to the present embodiment.
FIG. 7 is a repair vehicle diagram displayed on the display device of the vehicle repair cost estimation system according to the present embodiment.
FIG. 8 is a diagram for displaying the time for the attachment / detachment work of the repaired vehicle displayed on the display device of the vehicle repair cost estimation system according to the present embodiment;
FIG. 9 is a diagram for displaying a cost for correcting or replacing a repaired vehicle displayed on the display device of the vehicle repair cost estimating system according to the present embodiment;
FIG. 10 is a flowchart showing the operation principle of the vehicle repair instruction system according to the present embodiment.
[Explanation of symbols]
1 ... Personal computer
1a: Central processing unit
1b ... Main memory device
2 ... I / O interface
3 ... Auxiliary storage device
4 ... Input device
5 ... Gaze input digital still camera
6 ... Display device
7 ... Printing device
8: Communication device
40: Image storage unit
41 ... Image sensor
44 ... MPU
45 ・ ・ ・ Interface

Claims (3)

In a vehicle repair cost estimation system that estimates the repair cost of a repaired vehicle using a programmed computing device,
An image sensor for detecting a line-of-sight position on a secondary plane of an image, and a photographer's line-of-sight position for photographing a repair vehicle based on the line-of-sight position data detected by the image sensor. And a line-of-sight input digital still camera device that has an image storage unit that stores captured image data and outputs the damaged portion detection data and the captured image data stored in the image storage unit as repair vehicle data;
Work index data group which is the basis for calculating vehicle parts price and labor required for replacement or correction of this part, and replacement, detachment, correction, adjustment etc. are required according to the damaged part and damage degree of the vehicle A storage device storing vehicle attribute data such as correspondence data with
An input device for inputting repair vehicle data necessary for repair cost calculation,
A display device for displaying graphics and various data;
The vehicle attribute data corresponding to the repaired vehicle is retrieved from the vehicle attribute data stored in the previous storage device, and the repaired vehicle data is damaged by using the repaired vehicle data input based on the output of the line-of-sight input digital still camera device. A central processing unit for identifying a position, a damage range and a deformation amount or at least one of them, and calculating a repair cost of the repaired vehicle ,
The central processing unit causes the display device to display repair vehicle data related to the repair vehicle and vehicle attribute data corresponding to the repair vehicle or at least one of them, and based on the vehicle attribute data and the repair vehicle data A vehicle repair cost estimation system, wherein repair cost estimation is performed and displayed on the display device . In a vehicle repair cost estimation system that estimates the repair cost of a repaired vehicle using a programmed computing device,
An image sensor for detecting a line-of-sight position on a secondary plane of an image, and a photographer's line-of-sight position for photographing a repair vehicle based on the line-of-sight position data detected by the image sensor. And a line-of-sight input digital still camera device that has an image storage unit that stores captured image data and outputs the damaged portion detection data and the captured image data stored in the image storage unit as repair vehicle data;
Work index data group which is the basis for calculating vehicle parts price and labor required for replacement or correction of this part, and replacement, detachment, correction, adjustment etc. are required according to the damaged part and damage degree of the vehicle Storage device storing vehicle attribute data such as correspondence data with non-damaged vehicle image data corresponding to a repair vehicle,
An input device for inputting repair vehicle data necessary for repair cost calculation,
A display device for displaying graphics and various data;
The vehicle attribute data corresponding to the repaired vehicle is retrieved from the vehicle attribute data stored in the previous storage device, and the repaired vehicle data is damaged by using the repaired vehicle data input based on the output of the line-of-sight input digital still camera device. A central processing unit for determining a position, a damage range and a damage degree or at least one of them, and calculating a repair cost of the repaired vehicle ,
The central processing unit, the repair of at least one repair vehicle data and of the vehicle attribute data or those corresponding to the repair vehicle about the vehicle is displayed on the display device, wherein the non-damaged vehicle image data and the repair vehicle data And calculating at least one of the damage position, damage range and damage degree of the repaired vehicle, estimating the repair cost based on the vehicle attribute data and the repaired vehicle data, and displaying the repair cost on the display device. A vehicle repair cost estimation system characterized by that.  The repair vehicle data is composed of damaged portion detection data based on a plurality of line-of-sight positions, the line segments connecting the line-of-sight positions are used as damaged portion detection data, and the closed section is contoured with the line segments connecting the line-of-sight positions 3. The vehicle repair cost estimation system according to claim 1, wherein the range is damaged portion detection data.

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