INDENTATION HARDNESS TEST SYSTEM HAVING AN AUTOLEARNING SHADING CORRECTOR

• US 20140267679A1
• Filed: 03/13/2013
• Published: 09/18/2014
• Est. Priority Date: 03/13/2013
• Status: Abandoned Application

• Current Assignee: LECO Corporation
• Original Assignee: LECO Corporation
• Inventors: Hauck, John M., Barringham, James W. Jr.
• Application Number:
  US13/799,020
• Publication Number:
  US 20140267679A1
• Time in Patent Office: Days
• US Class Current: 348/86
• CPC Class Codes: G06T 2207/10056 Microscopic image
• CPC Class Codes: G06T 2207/30136 Metal
• CPC Class Codes: G06T 5/94 based on local image properties, e.g. for local contrast enhancement
• CPC Class Codes: G06V 10/20 Image preprocessing

Abstract

An indentation hardness test system is provided that includes: a frame including an attached indenter; a movable stage for receiving a part attached to the frame; a camera; a display; a processor; and a memory subsystem. The processor performs the steps of: (a) capturing images of different portions of the part; (b) for each image, computing an average intensity; (c) computing an average intensity across all images; (d) for each pixel, computing PixelAverageDelta_n(x,y) as a function of the raw pixel data and the average pixel intensity of the image frame; (e) for each pixel, computing a correction factor using the average intensity across all images and PixelAverageDelta_n(x,y); (f) performing shading correction by adjusting the raw pixel values by corresponding correction factors; and (g) generating a composite image of the part. Steps (b)-(e) may be performed on moving images while not including stationary images in the computations of those steps.

Claims

1. An indentation hardness test system for testing hardness of a test object, the system comprising:

a frame including an attached indenter;

a movable stage for receiving a part attached to the frame;

a camera for capturing images of the part;

a display;

a processor electrically coupled to the movable stage, the camera and the display; and

a memory subsystem coupled to the processor, the memory subsystem storing code that when executed instructs the processor to perform the steps of;

(a) causing the camera to capture a series of magnified image frames of different portions of the part, where each image frame includes raw pixel data for each pixel;

(b) for each captured image frame, computing an average pixel intensity of the image frame;

(c) computing an average pixel intensity across all captured image frames;

(d) for each pixel, computing PixelAverageDelta_n(x,y) as a function of the raw pixel data and the average pixel intensity of the image frame;

(e) for each pixel, computing and storing a correction factor using the average pixel intensity across all captured image frames as determined in step (c) and PixelAverageDelta_n(x,y) as determined in step (d);

(f) for each pixel, performing shading correction by adjusting the raw pixel value by a corresponding correction factor as determined in step (e); and

(g) generating a composite image of the part on the display, wherein the composite image includes the series of image frames as corrected for shading in step (f) and assembled according to relative positions of the image frames.

2. The indentation hardness test system of claim 1, wherein step (a) of capturing a series of magnified image frames includes obtaining, for each image frame n, raw pixel data Pixel_n(x,y) for each pixel location (0,0) through (X,Y), where X is a total number of rows of pixels and Y is a total number of columns of pixels within the image frame.

3. The indentation hardness test system of claim 2, wherein, in step (b), the average pixel intensity FrameAverage_n for each image frame n is computed as follows:

4. The indentation hardness test system of claim 3, wherein, in step (c), the average pixel intensity across all captured image frames FrameHistoricAverage_n is computed using the following equation:

5. The indentation hardness test system of claim 4, wherein, in step (d), PixelAverageDelta_n(x,y) is computed for each pixel as follows:

6. The indentation hardness test system of claim 5, wherein, in step (e), the correction factor CorrectionFactor_n(x,y) is computed for each pixel of the n^th image frame as follows:

7. The indentation hardness test system of claim 6, wherein step (f) further includes computing a corrected pixel value CorrectedPixel_n(x,y) for each pixel of the n^th image frame by:

CorrectedPixel_n(x,y)=Pixel_n(x,y)×

CorrectionFactor_n(x,y).

8. The indentation hardness test system of claim 1, wherein the code stored in the memory subsystem, when executed, instructs the processor to perform the step of:

obtaining associated stage coordinates for each of the captured image frames, wherein the composite image of the part is generated by assembling the captured image frames according to the associated stage coordinates.

9. The indentation hardness test system of claim 1, wherein steps (b)-(e) are only performed on image frames that are detected as moving.

10. A method for providing a composite image of a part with shading correction, comprising the steps of:

(a) capturing a series of magnified image frames of different portions of the part, where each image frame includes raw pixel data for each pixel;

(b) for each captured image frame, computing an average pixel intensity of the image frame;

(c) computing an average pixel intensity across all captured image frames;

(d) for each pixel, computing PixelAverageDelta_n(x,y) as a function of the raw pixel data and the average pixel intensity of the image frame;

(e) for each pixel, computing and storing a correction factor using the average pixel intensity across all captured image frames as determined in step (c) and PixelAverageDelta_n(x,y) as determined in step (d);

(f) for each pixel, performing shading correction by adjusting the raw pixel value by a corresponding correction factor as determined in step (e); and

(g) generating a composite image of the part, wherein the composite image includes the series of image frames as corrected for shading in step (f) and assembled according to relative positions of the image frames.

11. The method of claim 10, wherein step (a) of capturing a series of magnified image frames includes obtaining, for each image frame n, raw pixel data Pixel_n(x,y) for each pixel location (0,0) through (X,Y), where X is a total number of rows of pixels and Y is a total number of columns of pixels within the image frame.

12. The method of claim 11, wherein, in step (b), the average pixel intensity FrameAverage_n for each image frame n is computed as follows:

13. The method of claim 12, wherein, in step (c), the average pixel intensity across all captured image frames FrameHistoricAverage_n is computed using the following equation:

14. The method of claim 13, wherein, in step (d), PixelAverageDelta_n(x,y) is computed for each pixel as follows:

15. The method of claim 14, wherein, in step (e), the correction factor CorrectionFactor_n(x,y) is computed for each pixel of the n^th image frame as follows:

16. The method of claim 15, wherein step (f) further includes computing a corrected pixel value CorrectedPixel_n(x,y) for each pixel of the n^th image frame by:

CorrectedPixel_n(x,y)=Pixel_n(x,y)×

CorrectionFactor_n(x,y).

17. The method of claim 10, wherein steps (b)-(e) are only performed on image frames that are detected as moving.

18. A non-transitory computer readable medium having stored thereon software instructions that, when executed by a processor, cause the processor to provide a composite image of a part with shading correction, by executing the steps comprising:

(a) capturing a series of magnified image frames of different portions of the part, where each image frame includes raw pixel data for each pixel;

(b) for each captured image frame, computing an average pixel intensity of the image frame;

(c) computing an average pixel intensity across all captured image frames;

(d) for each pixel, computing PixelAverageDelta_n(x,y) as a function of the raw pixel data and the average pixel intensity of the image frame;

(e) for each pixel, computing and storing a correction factor using the average pixel intensity across all captured image frames as determined in step (c) and PixelAverageDelta_n(x,y) as determined in step (d);

(f) for each pixel, performing shading correction by adjusting the raw pixel value by a corresponding correction factor as determined in step (e); and

(g) generating a composite image of the part, wherein the composite image includes the series of image frames as corrected for shading in step (f) and assembled according to relative positions of the image frames.

19. The non-transitory computer readable medium of claim 18, wherein step (a) of capturing a series of magnified image frames includes obtaining, for each image frame n, raw pixel data Pixel_n(x,y) for each pixel location (0,0) through (X,Y), where X is a total number of rows of pixels and Y is a total number of columns of pixels within the image frame.

20. The non-transitory computer readable medium of claim 19, wherein, in step (b), the average pixel intensity FrameAverage_n for each image frame n is computed as follows:

21. The non-transitory computer readable medium of claim 20, wherein, in step (c), the average pixel intensity across all captured image frames FrameHistoricAverage_n is computed using the following equation:

22. The non-transitory computer readable medium of claim 21, wherein, in step (d), PixelAverageDelta_n(x,y) is computed for each pixel as follows:

23. The non-transitory computer readable medium of claim 22, wherein, in step (e), the correction factor CorrectionFactor_n(x,y) is computed for each pixel of the n^th image frame as follows:

24. The non-transitory computer readable medium of claim 23, wherein step (f) further includes computing a corrected pixel value CorrectedPixel_n(x,y) for each pixel of the n^th image frame by:

CorrectedPixel_n(x,y)=Pixel_n(x,y)×

CorrectionFactor_n(x,y).

25. The non-transitory computer readable medium of claim 18, wherein steps (b)-(e) are only performed on image frames that are detected as moving.