System and method for automatically measuring the dimensions of and identifying the type of exterior siding

• US 9,256,932 B1
• Filed: 05/20/2015
• Issued: 02/09/2016
• Est. Priority Date: 03/28/2014
• Status: Active Grant

• Current Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Original Assignee: State Farm Mutual Automobile Insurance Company (State Farm)
• Inventors: Maurer, Jonathan D., Christopulos, Nicholas U.
• Primary Examiner(s): Hung, Yubin
• Application Number:
  US14/717,051
• Time in Patent Office: 265 Days
• Field of Search: 382/141, 382/286, 348/137
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/10004 Still image; Photographic image
• CPC Class Codes: G06T 2207/20048 Transform domain processing
• CPC Class Codes: G06T 2207/20061 Hough transform
• CPC Class Codes: G06T 2207/30108 Industrial image inspection
• CPC Class Codes: G06T 7/001 using an image reference approach
• CPC Class Codes: G06T 7/13 Edge detection
• CPC Class Codes: G06T 7/60 Analysis of geometric attributes
• CPC Class Codes: G06T 7/62 of area, perimeter, diameter or volume
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning

Abstract

Methods, systems, and computer readable media are disclosed for determining a pixel-to-length ratio between a number of pixels disposed over a predetermined length of a reference object within an image of a siding sample and the predetermined length of the reference object. A first and second distance between respective first and second pairs of points within the image corresponding to respective first and second length measurements of the siding sample are determined, as well as a first and second number of pixels disposed between the first and second pair of points, respectively. Furthermore, the method, system, and computer readable medium disclose determining the first length measurement based on the pixel-to-length ratio and the first number of pixels, determining the second length measurement based on the pixel-to-length ratio and the second number of pixels, and identifying a siding product associated with the first and second length measurements.

Claims

1. A mobile computing device, comprising:

an image capture device configured to capture an image of a siding sample including a reference object; and

a central processing unit (CPU) configured to;

adjust an orientation of the reference object within the image of the siding sample to align edges of the reference object with edges of the siding sample and to provide an aligned reference object;

measure a dimension of the aligned reference object in terms of pixels;

measure a first dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a first number of pixels spanned by the first dimension of the siding sample within the image of the siding sample; and

identify a siding product associated with the first dimension of the siding sample.

2. The mobile computing device of claim 1, wherein the CPU is further configured to identify the siding product associated with the first dimension of the siding sample by communicating with a computing device.

3. The mobile computing device of claim 1, wherein the CPU is further configured to adjust the orientation of the reference object only when the CPU determines that the orientation needs to be adjusted.

4. The mobile computing device of claim 1, wherein the CPU is further configured to rectify the image of the siding sample so the perspective of the siding sample faces forward if the reference object includes perspective distortion.

5. The mobile computing device of claim 1, wherein the CPU is further configured to adjust the orientation of the reference object such that respective horizontal and vertical edges of each of the aligned reference object and the siding sample are aligned with edges corresponding to a horizontal-vertical plane.

6. The mobile computing device of claim 1, wherein the CPU is further configured to measure a second dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a second number of pixels spanned by the second dimension of the siding sample within the image of the siding sample and to identify the siding product based upon the first and second dimensions.

7. The mobile computing device of claim 6, wherein:

the first dimension of the siding sample corresponds to a face dimension,

the second dimension of the siding sample corresponds to a profile dimension, and

the CPU is further configured to identify the siding product stored in a siding product reference database having a face dimension and a profile dimension matching the first dimension and the second dimension of the siding sample, respectively.

8. The mobile computing device of claim 1, wherein the CPU is further configured to detect the reference object using at least one of:

a Scale-Invariant Feature Transform (SIFT);

a Speeded Up Robust Features (SURF);

a Radon transform;

or

a Hough transform.

9. A computer-implemented method for identifying a siding product, comprising:

adjusting, by one or more processors, an orientation of a reference object within a captured image of a siding sample to align edges of the reference object with edges of the siding sample and to provide an aligned reference object;

measuring, by one or more processors, a dimension of the aligned reference object in terms of pixels;

measuring, by one or more processors, a first dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a first number of pixels spanned by the first dimension of the siding sample within the image of the siding sample; and

identifying, by one or more processors, a siding product associated with the first dimension of the siding sample.

10. The method of claim 9, wherein the act of adjusting comprises:

determining, by one or more processors, whether the orientation of the reference object needs to be adjusted, and

wherein the act of adjusting the orientation of the reference object comprises;

adjusting the orientation of the reference object only when the one or more processors determine that the orientation needs to be adjusted.

11. The method of claim 9, further comprising:

rectifying, by one or more processors, the image of the siding sample so the perspective of the siding sample faces forward if the reference object includes perspective distortion.

12. The method of claim 9, wherein the act of adjusting the orientation of the reference object comprises:

adjusting the orientation of the reference object such that respective horizontal and vertical edges of each of the aligned reference object and the siding sample are aligned with edges corresponding to a horizontal-vertical plane.

13. The method of claim 9, further comprising:

measuring, by one or more processors, a second dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a second number of pixels spanned by the second dimension of the siding sample within the image of the siding sample, and

wherein the act of identifying the siding sample further comprises;

identifying the siding product based upon the first and second dimensions.

14. The method of claim 13, wherein:

the first dimension of the siding sample corresponds to a face dimension,

the second dimension of the siding sample corresponds to a profile dimension, and

the act of identifying the siding sample further comprises;

identifying the siding product stored in a siding product reference database having a face dimension and a profile dimension matching the first dimension and the second dimension of the siding sample, respectively.

15. The method of claim 9, further comprising:

detecting, by one or more processors, the reference object using at least one of;

a Scale-Invariant Feature Transform (SIFT);

a Speeded Up Robust Features (SURF);

a Radon transform;

or

a Hough transform.

16. A non-transitory, tangible computer-readable medium storing machine readable instructions that, when executed by a processor, cause the processor to:

adjust an orientation of a reference object within a captured image of a siding sample to align edges of the reference object with edges of the siding sample and to provide an aligned reference object;

measure a dimension of the aligned reference object in terms of pixels;

measure a first dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a first number of pixels spanned by the first dimension of the siding sample within the image of the siding sample; and

identify a siding product associated with the first dimension of the siding sample.

17. The non-transitory, tangible computer-readable medium of claim 16, further storing instructions that, when executed by the processor, cause the processor to:

determine whether the orientation of the reference object needs to be adjusted, and

wherein the instructions to adjust the orientation of the reference object further include instructions, that when executed by the processor, cause the processor to;

adjust the orientation of the reference object only when it is determined that the orientation needs to be adjusted.

18. The non-transitory, tangible computer-readable medium of claim 16, further storing instructions that, when executed by the processor, cause the processor to:

rectify the image of the siding sample so the perspective of the siding sample faces forward if the reference object includes perspective distortion.

19. The non-transitory, tangible computer-readable medium of claim 16, wherein the instructions to adjust the orientation of the reference object further include instructions, that when executed by the processor, cause the processor to:

adjust the orientation of the aligned reference object such that respective horizontal and vertical edges of each of the aligned reference object and the siding sample are aligned with edges corresponding to a horizontal-vertical plane.

20. The non-transitory, tangible computer-readable medium of claim 16, further including instructions that when executed by the processor, cause the processor to:

measure a second dimension of the siding sample based upon the dimension of the aligned reference object in terms of pixels and a second number of pixels spanned by the second dimension of the siding sample within the image of the siding sample, and

wherein the instructions to identify the siding product further include instructions that, when executed by the processor, cause the processor to identify the siding product based upon the first and second dimensions.

21. The non-transitory, tangible computer-readable medium of claim 20, wherein:

the first dimension of the siding sample corresponds to a face dimension,

the second dimension of the siding sample corresponds to a profile dimension, and

the act of identifying the siding sample further comprises;

identifying the siding product stored in a siding product reference database having a face dimension and a profile dimension matching the first dimension and the second dimension of the siding sample, respectively.

22. The non-transitory, tangible computer-readable medium of claim 16, further storing instructions that, when executed by the processor, cause the processor to:

detect the reference object using at least one of;

a Scale-Invariant Feature Transform (SIFT);

a Speeded Up Robust Features (SURF);

a Radon transform;

or

a Hough transform.