Methods for inspecting surface damage

Abstract

To provide a surface flaw inspection method that can accurately detect a white flaw.SOLUTION: A surface flaw inspection method includes: extracting a black, long and narrow defect candidate area from an inspection image (S102); creating rectangular areas respectively on both ends of the black, long and narrow defect candidate area (S104); extracting a white defect candidate area from an inspection image of the rectangular areas (S106); and detecting a white defect on the basis of the size of the white defect candidate area (S109, S110).SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method for inspecting surface defects.

Background Art

[0002] Patent Document 1 describes a surface defect inspection apparatus that detects white defects existing around a black defect.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] Black]]Black (deep) and elongated defects often have white (shallow) defects formed at their ends. However, in Patent Document 1, there is a problem that there is no specific method for detecting white defects within the end region of the elongated defect.

Means for Solving the Problems

[0005] A surface defect inspection method according to an embodiment detects white defects within a region formed at the end of a black and elongated defect as follows.

Effects of the Invention

[0006] According to the surface defect inspection method of the present disclosure, white defects can be detected with high accuracy.

Brief Description of the Drawings

[0007] [Figure 1] It is a flowchart showing an example of the surface defect inspection method according to the present embodiment. [Figure 2] It is a diagram showing an example of image processing of surface defects in the surface defect inspection method according to the present embodiment. [Figure 3]This figure shows an example of image processing for surface scratches in the surface scratch inspection method according to this embodiment. [Modes for carrying out the invention]

[0008] This embodiment Embodiments of the present invention will be described below with reference to the drawings. Figure 1 is a flowchart showing an example of a surface scratch inspection method according to this embodiment. Figure 2 is a diagram showing an example of image processing of surface scratches.

[0009] First, in step S101, the inspection image is input to the inspection device. An example of the input image is shown in Figure 2a. Then the process proceeds to step S102. Here, the inspection device has a computing device that performs image analysis.

[0010] Next, in step S102, the inspection image is binarized. Then, candidate defect regions are extracted from the binarized inspection image. An example of the extracted image is shown in Figure 2b. In Figure 2b, the candidate defect regions are regions b1 and b2. Then the process proceeds to step S103. Regions b1 and b2 are also used in image processing in step S107.

[0011] In step S103, the size of the black, elongated defect candidate region is obtained from the defect candidate region. Then the process proceeds to step S104.

[0012] In step S104, rectangular regions are created at both ends of the candidate area for the black, elongated defect. An example of an image of the rectangular regions is shown in Figure 2c. The rectangular regions are c11, c12, c21, and c22. Then the process proceeds to step S105.

[0013] In step S105, the inspection image is cropped into a rectangular area. An example of an inspection image cropped into a rectangular area is shown in Figure 2, d. The inspection images cropped into rectangular areas are d11, d12, d21, and d22. Then the process proceeds to step S106.

[0014] In step S106, the inspection image cut out in the rectangular region is binarized. Then, white defect candidate regions are extracted from the binarized inspection image. An example of the extracted image is shown in e of FIG. 2. The white defect candidate regions are regions e1 and e2. Then, the process proceeds to step S107.

[0015] In step S107, the image extracted in step S102 (image of the black and elongated defect candidate region) and the image extracted in step S106 (image of the white defect candidate region) are combined. An example of the extracted image is shown in f of FIG. 2. The white defect candidate regions are regions f1 and f2. Then, the process proceeds to step S108.

[0016] In step S108, the size information of regions f1 and f2 shown in f of FIG. 2 is acquired. Then, the process proceeds to step S109.

[0017] In step S109, it is determined whether the widths of regions f1 and f2 are greater than a specified size. If the width of the region is greater than the specified size, the process proceeds to step S110. If the width of the region is less than or equal to the specified size, it is determined that the region is not a defect, and the process ends.

[0018] In step S110, it is determined whether the lengths of regions f1 and f2 are greater than a specified size. If the length of the region is greater than the specified size, it is determined that the region is a defect, and the process ends. If the length of the region is less than or equal to the specified size, it is determined that the region is not a defect, and the process ends.

[0019] Through the above processing, the inspection of surface scratches is performed. Next, the details of steps S103 and S104 will be described. FIG. 3 is a diagram showing an example of image processing of surface scratches in the surface scratch inspection method according to the present embodiment.

[0020] By sequentially executing the following processes corresponding to a to g in FIG. 3, the rectangular region in step S104 is created. a: Calculate the length (l) obtained by dividing the length (L) of the black and elongated defect into three parts b: Rectangularly approximate the black, slender defect region to obtain the angle (θ), the length (m) of the long side, and the centroid coordinates (p). ⇒ Use the trigonometric method to calculate two points (p1, p2) corresponding to both ends of the black, slender defect. c: Use the coordinates of p1 and p2 obtained in b, the angle (θ), the long side, and the length (l) divided into three parts calculated in a to create rectangular regions at both ends of the black, slender region. d: Extract only the black, slender region within the rectangle created in c to obtain the centroid coordinates (p3, p4) ⇒ Calculate the increasing direction of the long side from the two points (p1, p2) calculated in b and the centroid coordinates (p3, p4) of the black, slender defect region. e: Rectangularly approximate the extracted black, slender region in d to obtain the angles (θ1, θ2) and the lengths (n1, n2) of the long sides. f: Use the angles (θ1, θ2) and the lengths (n1, n2) of the long sides obtained in e to calculate two points p3’ and p4’, and create a region in the increasing direction calculated in d. g: Combine the regions in e and f.

[0021] Thus, according to the surface defect inspection method of the present embodiment, since black (deep) and slender scratches often have white (shallow) scratches formed at their ends, by detecting the scratches in the regions formed at the ends, white scratches can be accurately detected.

[0022] Note that the present invention is not limited to the above embodiment and can be appropriately changed without departing from the gist. For example, each process described in the drawings as a flowchart for performing various processes can be configured by a CPU, a memory, and other circuits in terms of hardware, and can be realized by a program loaded into the memory or the like in terms of software. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by hardware, software, or a combination thereof, and are not limited to any one of them.

[0023] Furthermore, the programs described above can be stored and supplied to a computer using various types of non-temporary computer-readable media. Non-temporary computer-readable media include various types of tangible recording media. Examples of non-temporary computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memory (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). Programs may also be supplied to a computer by various types of temporary computer-readable media. Examples of temporary computer-readable media include electrical signals, optical signals, and electromagnetic waves. Temporary computer-readable media can be supplied to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

Claims

[Claim 1] Extract a black, elongated defect candidate region from the inspection image. Rectangular regions are created at both ends of the aforementioned black, elongated defect candidate region. From the inspection image of the aforementioned rectangular region, a white defect candidate region is extracted. A surface scratch inspection method for detecting defects based on the size of a defect candidate region obtained by combining the aforementioned black, elongated defect candidate region and the aforementioned white defect candidate region.

Images