SYSTEMS AND METHODS TO DETECT A SCRATCH
Systems and methods to detect a scratch are provided. The method includes identifying, via an OPTICS technique, a cluster of points on an image. The method also includes utilizing a principal curves technique to identify a curve that approximates one or more points of the cluster of points as a smooth curve. The method further includes determining one or more characteristics of the curve. The method further includes determining one or more characteristics of the cluster. The method further includes identifying a scratch based on at least one of the one or more characteristics of the curve and the one or more characteristics of the cluster.
1 . A computer-implemented method to detect a scratch, comprising:
identifying, via an OPTICS technique, a cluster of points on an image;
utilizing a principal curves technique to identify a curve that approximates one or more points of the cluster of points as a smooth curve;
determining one or more characteristics of the curve;
determining one or more characteristics of the cluster; and
identifying a scratch based on at least one of the one or more characteristics of the curve and the one or more characteristics of the cluster.
2 . The computer-implemented method of claim 1 , wherein identifying, via the OPTICS technique, the cluster of points comprises identifying, via the OPTICS technique, one or more overlapping clusters of points, wherein each cluster of points of the one or more overlapping clusters of points is within a threshold distance of one or more other clusters of points of the overlapping clusters of points.
3 . The computer-implemented method of claim 1 , further comprising extracting the cluster of points from the image before the curve is identified.
4 . The computer-implemented method of claim 1 , further comprising determining a distance from the curve to a point of the cluster, wherein determining the one or more characteristics of the cluster comprises determining the one or more characteristics of the cluster based on the distance from the curve to the point.
5 . The computer-implemented method of claim 1 , further comprising determining a width of the cluster, wherein one of the one or more characteristics of the cluster is the width of the cluster.
6 . The computer-implemented method of claim 1 , further comprising determining a ratio of a length of the curve to a width of the cluster, wherein one of the one or more characteristics of the cluster is the ratio of the length of the curve to the width of the cluster.
7 . The computer-implemented method of claim 1 , further comprising determining a length of the curve, wherein one of the one or more characteristics of the curve is the length of the curve.
8 . The computer-implemented method of claim 1 , further comprising determining a curvature of the curve, wherein one of the one or more characteristics of the curve is the curvature of the curve.
9 . The computer-implemented method of claim 1 , further comprising identifying a pattern associated with the scratch based on the one or more characteristics of the curve.
10 . The computer-implemented method of claim 1 , further comprising:
identifying, via the OPTICS technique, a second cluster of points on the image;
utilizing the principal curves technique to identify a second curve that approximates one or more points of the second cluster of points as a second smooth curve;
determining one or more characteristics of the second curve;
determining one or more characteristics of the second cluster; and
identifying a second scratch based on at least one of the one or more characteristics of the second curve and the one or more characteristics of the second cluster.
11 . The computer-implemented method of claim 1 , further comprising:
identifying, via the OPTICS technique, a second cluster of points on second image;
utilizing the principal curves technique to identify a second curve that approximates one or more points of the second cluster of points as a second smooth curve;
determining one or more characteristics of the second curve;
determining one or more characteristics of the second cluster; and
identifying a second scratch based on at least one of the one or more characteristics of the second curve and the one or more characteristics of the second cluster.
12 . A scratch detection system, comprising:
a storage medium; and
one or more processors configured to:
identify, via an OPTICS technique, a cluster of points on an image;
utilize a principal curves technique to identify a curve that approximates one or more points of the cluster of points as a smooth curve;
determine one or more characteristics of the curve;
determine one or more characteristics of the cluster; and
identify a scratch based on at least one of the one or more characteristics of the curve and the one or more characteristics of the cluster.
13 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to extract the cluster of points from the image before the curve is identified.
14 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to determine a distance from the curve to a point of the cluster, wherein from the curve to a point of the cluster is one of the one or more characteristics of the cluster.
15 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to determine a width of the cluster, wherein the width of the cluster is one of the one or more characteristics of the cluster.
16 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to determine a ratio of a length of the curve to a width of the cluster, wherein the ratio of the length of the curve to the width of the cluster is one of the one or more characteristics of the cluster.
17 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to:
identify, via the OPTICS technique, a second cluster of points on the image;
utilize the principal curves technique to identify a second curve that approximates one or more points of the second cluster of points as a second smooth curve;
determine one or more characteristics of the second curve;
determine one or more characteristics of the second cluster; and
identify a second scratch based on at least one of the one or more characteristics of the second curve and the one or more characteristics of the second cluster.
18 . The scratch detection system of claim 12 , wherein the one or more processors are further configured to:
identify, via the OPTICS technique, a second cluster of points on second image;
utilize the principal curves technique to identify a second curve that approximates one or more points of the second cluster of points as a second smooth curve;
determine one or more characteristics of the second curve;
determine one or more characteristics of the second cluster; and
identify a second scratch based on at least one of the one or more characteristics of the second curve and the one or more characteristics of the second cluster.
19 . A non-transitory computer-readable medium comprising instructions, which when executed by a processor, causes the processor to perform operations comprising:
identifying, via an OPTICS technique, a cluster of points on an image;
utilizing a principal curves technique to identify a curve that approximates one or more points of the cluster of points as a smooth curve;
determining one or more characteristics of the curve;
determining one or more characteristics of the cluster; and
identifying a scratch based on at least one of the one or more characteristics of the curve and the one or more characteristics of the cluster.
20 . The non-transitory computer-readable medium of claim 19 , wherein the instruction, when executed by the processor, causes the processor to perform operations comprising:
identifying, via an OPTICS technique, a second cluster of points on second image;
utilizing the principal curves technique to identify a second curve that approximates one or more points of the second cluster of points as a second smooth curve;
determining one or more characteristics of the second curve;
determining one or more characteristics of the second cluster; and
identifying a second scratch based on at least one of the one or more characteristics of the second curve and the one or more characteristics of the second cluster.