Process and system for analyzing deformations in motor vehicles

• US 8,515,152 B2
• Filed: 03/25/2005
• Issued: 08/20/2013
• Est. Priority Date: 05/11/2004
• Status: Active Grant

• Current Assignee: Fausto Siri
• Original Assignee: Fausto Siri
• Inventors: Siri, Fausto
• Primary Examiner(s): Punnoose, Roy M
• Application Number:
  US11/579,934
• Publication Number:
  US 20080267487A1
• Time in Patent Office: 3,070 Days
• Field of Search: 382/141
• US Class Current: 382/141
• CPC Class Codes: B60S 5/00 Servicing, maintaining, repairing, or refitting of vehicles vehicles adapted to carry a workshop for servicing or maintenance B60P3/14; servicing rail locomotives B61K
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 90/00 Systems or methods specially adapted for administrative, commercial, financial, managerial or supervisory purposes, not involving significant data processing

Abstract

A process for identifying, analysing and estimating deformations in motor vehicles is presented. The process includes loading image data relevant to at least a three-dimensional image of a damaged vehicle in memory, calling up image data of a sample vehicle from a database of sample vehicle images, the sample vehicle image corresponding to the damaged vehicle type, displaying image data relevant to the damaged vehicle image and the corresponding undamaged sample image, comparing the respective images to identify damage location or deformation and detecting deformed regions, computing at least one of area and volume of damaged or deformed region(s), and identifying the location in space of the damage on the vehicle using a defined algorithm and the results of said comparison.

Claims

1. A process for identifying, analysing and estimating deformations in motor vehicles, comprising:

loading image data relevant to at least a three-dimensional image of a damaged vehicle in a vehicle image memory;

accessing image data of at least a three-dimensional image of a sample vehicle from a database of sample vehicle images, said sample vehicle image being the image of a vehicle type corresponding to the damaged vehicle type;

displaying image data relevant to the damaged vehicle and to the corresponding sample vehicle type;

automatically comparing said three-dimensional image of the damaged vehicle with the corresponding three-dimensional image of the sample vehicle and (i) identifying damage location or deformation and (ii) detecting deformed regions by visually comparing both images;

indicating one or more of said damaged or deformed regions on at least one of the two images, said indicating including at least one of highlighting and delineation;

storing image data corresponding to said damaged or deformed regions of said damaged vehicle;

computing one or more of perimeter, area, volume and further morphologic parameters of said damaged or deformed region or regions;

identifying a spatial location of said vehicle damage operating on one or more of the deformed regions and the results of said comparison; and

computing labor times and costs for repairing the damaged or deformed regions, based at least in part on (i) said computed one or more of perimeter, area, volume of damaged or deformed region or regions and further morphologic parameters, and (ii) a database or repair times and costs.

2. Process according to claim 1, wherein the determination of the damaged region is carried out semi-automatically by an operator.

3. Process according to claim 1, wherein the damaged or deformed regions in displayed images are selected by drawing a close boundary line surrounding a vehicle image region coinciding with a damaged region and by tagging pixels within said boundary line as corresponding to a damaged or deformed region of vehicle.

4. Process according to claim 1, wherein comparison between the damaged vehicle and the sample vehicle is carried out automatically.

5. Process according to claim 4, wherein in automatic mode a comparison is made between image of damaged vehicle and image of sample vehicle, and damaged and/or deformed regions of said damaged vehicle being identified by differences between to damaged vehicle image and image data relevant to sample vehicle image.

6. Process according to claim 4, wherein the selection of sample vehicle image from a database of sample vehicle images is carried out automatically the image whose image data differ at a minimum extent from image data of damaged vehicle being selected as image of sample vehicle.

7. Process according to claim 4, wherein image data comprise a three-dimensional array, each element of said array being correlated to an image pixel of a two-dimensional image according to a plane passing through said pixel,

and wherein the comparison between image data of damaged vehicle and the comparison between image data of sample vehicle being constituted by comparison of image data that in the two image data arrays have the same location.

8. Process according to claim 4, wherein area and/or volume of image region relevant to vehicle image pixel coinciding with damaged region is computed, which region is determined by selection means and/or by automatically comparing image data of damaged vehicle with image data of sample vehicle.

9. Process according to claim 4, further comprising comparing image data relevant to pixels having the same position in each pixel set composing the image.

10. Process according to claim 9, further comprising computing the area of deformed region and/or deformation volume and/or deformation depth.

11. Process according to claim 4, wherein a virtual image of sample vehicle is produced constituting by the virtual image set of individual structural parts of vehicle forming independent structural units, that is individual vehicle parts, which virtual image can be displayed as image of assembled vehicle or as exploded vehicle image and/or as transparency image of damaged vehicle wherein images of hidden parts are also displayed, each structural part of vehicle being univocally identified by an identification code.

12. Process according to claim 11, wherein at least an external view of the vehicle is defined, various external views of vehicle taken from different sides thereof and/or in perspective and at least an inner view of vehicle, various inner views of vehicle similarly to external views, it being possible to graphically select one or more structural parts of vehicle for identificating thereof as damaged parts or one or more structural parts of vehicle being identified as damaged parts by automatic comparison between virtual images of the sample vehicle and virtual images of the damaged vehicle.

13. Process according to claim 1, wherein the image of the vehicle is produced by scanning means, particularly three-dimensional scanning means.

14. Process according to claim 13, wherein identification, analysis and estimation of the at least one damaged region is carried out automatically by acquiring the three-dimensional virtual image of the damaged vehicle by said scanning means and the comparison of acquired image data with image library data relevant to the sample vehicle.

15. Process according to claim 1, wherein damaged vehicle images and library ones of sample vehicle or vehicles are three-dimensional or vectorial images.

16. Process according to claim 1, wherein the automatic selection of sample vehicle and/or the automatic selection of damaged or deformed region or regions is either confirmed or not confirmed by an operator.

17. Process according to claim 1, wherein when identification/selection/computation of damaged or deformed areas and/or volumes finish a size and/or area and/or volume of damaged regions of a specific vehicle type are stored in the work program.

18. Process according to claim 1, wherein one or more images of the damaged vehicle are acquired from inside the damaged vehicle.

19. Process according to claim 1, wherein image data of at least a portion of structural parts of the sample vehicle are stored as dis-assemble and assemble parts, and displayed in at least one of an assembled state, an exploded state or transparently.

20. Process according to claim 1, wherein the structural part of vehicle is determined by determining the structural part wherein pixels fall coinciding with image regions identified as damaged and/or deformed regions, said structural parts being identified as damaged and/or deformed ones stored in a memory.

21. Process according to claim 1, further comprising providing a database of vehicle parts, each part being identified by a code.

22. Process according to claim 21, further comprising providing a time and/or cost database for repairing and replacing motor vehicle parts.

23. Process according to claim 21, wherein said motor vehicle part database for each motor vehicle part further includes a list of parts to be disassembled/reassembled for disassembling/reassembling each single part.

24. Process according to claim 1, further comprising for each vehicle part affected by the deformation or damage:

generating a degree of severity of the deformation proportional to the at least one of size, area, and volume of the damaged part.

25. Process according to claim 1, wherein for each different part identified as deformed or damaged part providing an estimate of cost and operations needed to rebuild the part itself, by comparison with times and costs database of motor vehicle parts.

26. Process according to claim 25, wherein said time and cost estimation is preferably divided into three steps:

sheet metal repair or processing, painting and part assembly/disassembly.

27. Process according to claim 23, wherein to each damaged part a time and/or cost estimation is associated, said estimation being automatically self chosen by said process, in a range of minimum estimation to maximum estimation of needed time and/or cost in proportion to the severity of deformation or damage.

28. Process according to claim 26, wherein the system sums costs/times needed for the three steps of each damaged vehicle part.

29. Process according to claim 28, wherein results are one of printed and displayed on a monitor.

30. Process according to claim 25, wherein said time and cost database of motor vehicle parts for each motor vehicle part has a minimum estimation and a maximum estimation of one or more of time and cost needed for each of sheet metal repair or processing, painting and part assembly/disassembly.

31. Process according to claim 25, wherein for each damaged part the system compares said costs/times sum needed for the repair with costs/times needed for completely replacing said damaged part with a new one.

32. Process according to claim 25, further comprising automatically choosing replacing said damaged or deformed part or repairing the same part based on one of lowest cost, time and some combination of cost and time.

33. Process according to claim 1, further comprising being communicably connected to a database of motor vehicle parts in a warehouse.

34. Process according to claim 33, further comprising comparing parts to be replaced with parts in the warehouse and producing a report with available and not available parts.

35. Process according to claim 33, further comprising producing an order by one of paper and electronically for supplying the warehouse with at least one of parts taken for replacement and parts not available.