1. AdeptSight Image Processing Tools Lee Haney January 21, 2010

2. Background information... I was raised in North Webster, Indiana.

3. Proof positive the rumor is false!!!

4. What are image processing tools? Most tools locate or measure. –Histogram/caliper –Line finder –Blob finder Image processing tool modifies an image. –Input image is acted upon by tool. –New image buffer is the result. –Some operations require two images. –Multiple tools can be combined. Input Image New Image Operation

5. Why use them? Locator tool may be insufficient –Variably-shaped part Poor illumination –Uneven lighting surface Need to enhance or modify features

6. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

7. Tool Parameters Operation Source image Operand image Scaling Clipping Data type

8. Scaling Occurs after tool operation. Each resulting pixel is multiplied by scale factor. Scaling factor can range from 0-10,000 Not all operations support scaling.

9. Clipping Computations can result in new values which extend past data type boundaries. Performed after image processing and scaling. Normal clipping –Result < minimum, set output to minimum. –Result > maximum, set output to maximum. Absolute clipping –Absolute value of result –Result > maximum, set output to maximum.

10. AdeptSight 3 Considerations Data types –Unsigned 8-bit integer (0-255) –Signed 16-bit integer –Signed 32-bit integer –However, stick to the default 8-bit integer. Cannot work on color images

11. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

12. Assignment Operations Initialization –Output image pixels are set to constant value. –Specify image size. Copy –Input image is copied to output image. Inversion –Input pixels are inverted (255-pixel). No scaling and clipping is needed.

13. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

14. Arithmetic Operations Two modes for usage. –Input image and operand image. –Input image and constant. Addition Subtraction Multiplication Division Lightest – Maximum value used. Darkest – Minimal value used. Scaling and clipping are options.

15. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

16. Logical Operations Requires two images of same size. Logical operator performed on pixel by pixel basis. Supported operations –AND –NAND –OR –NOR –XOR No scaling and clipping option.

17. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

18. Filtering Basics Neighboring pixels in input image are processed to determine value of output pixel. Kernel specifies size of neighborhood and the weighting of each pixel.

19. Averaging Kernel Pixel from input image is replaced in output image by the average of all pixels in kernel. Removes noise and blurs edges. 3x3 111 111 111 5x5 11111 11111 11111 11111 11111 7x7 1111111 1111111 1111111 1111111 1111111 1111111 1111111

20. Gaussian Kernel Acts like a low-pass filter. Removes noise. Blurs image. 3x3 121 242 121 5x5 271272 73152317 12521275212 73152317 271272 7x7 1122211 1345431 2478742 25810852 2478742 1345431 1122211

21. Horizontal Prewitt Kernel Detects horizontal gradients or edges. Typically used with absolute clipping. May need to scale. 3x3 111 000

22. Vertical Prewitt Kernel Detects vertical gradients or edges. Typically used with absolute clipping. May need to scale. 3x3 01 01 01

23. Sobel Horizontal Kernel Responds to horizontal edges. Typically use in absolute clipping mode. May need to scale. 3x3 121 000 -2 5x5 14741 21017102 00000 -2-10-17-10-2 -4-7-4 7x7 14913941 311263426113 313304030133 0000000 -3-13-30-40-30-13-3 -11-26-34-26-11-3 -4-9-13-9-4

24. Sobel Vertical Kernel Responds to vertical edges. Typically use in absolute clipping mode. May need to scale. 3x3 01 -202 01 5x5 -2021 -4-100104 -7-170177 -4-100104 -2021 7x7 -3 0331 -4-11-13013114 -9-26-30030269 -13-34-400403413 -9-26-30030269 -4-11-13013114 -3 0331

25. Laplacian Kernel Circular gradient filter. Highlights all edges. Typically use in absolute clipping mode. 3x3 8 5x5 -3-4-3 -3060 -46206-4 -3060 -3-4-3 7x7 -2-3-4-6-4-3-2 -3-5-4-3-4-5-3 -4 9209-4 -6-3203620-3-6 -4 9209-4 -3-5-4-3-4-5-3 -2-3-4-6-4-3-2

26. Sharpen Kernel Output pixels are the subtraction of the average of the input image pixels. 3x3 9 5x5 25 7x7 49

27. SharpenLow Kernel Sharpens and smooths at the same time. 3x3 16 5x5 -3-4-3 -3060 -46406-4 -3060 -3-4-3 7x7 -2-3-4-6-4-3-2 -3-5-4-3-4-5-3 -4 9209-4 -6-3207220-3-6 -4 9209-4 -3-5-4-3-4-5-3 -2-3-4-6-4-3-2

28. Median Filter Output pixel is equal to the input image’s neighborhood median. Reduces impulsive noise. Doesn’t destroy edges by blurring as an averaging filter does. Non-linear filter

29. Custom Kernel Define kernel that you want. Currently no way to define this kernel. Not sure if this will be supported.

30. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

31. Dilate Operation Output pixel is replaced by highest grey value of kernel neighborhood. Results in expanded of bright regions. Operation is typically iterated. Useful for connecting broken regions. AdeptSight kernel is limited to 3x3.

32. Erode Operation Output pixel is replaced by lowest grey value of kernel neighborhood. Results in expanded of dark regions. Operation is typically iterated. Useful for removing thin light areas. AdeptSight kernel is limited to 3x3.

33. Close Operation Equivalent to a dilate operation followed by an erode operation. Has the effect of removing small dark particles and holes

34. Open Operation Equivalent to an erode operation followed by a dilate operation. Has effect of removing peaks from an image, leaving only the image background.

35. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

36. Equalization Operation Enhances the input image by flattening the histogram of the input image. Equalization is more beneficial for human viewers than machine vision.

37. Stretching Operation Increases the contrast an image. Applies a simple piecewise linear intensity transformation based on the input image’s histogram.

38. Light/Dark Threshold Operations Operation compares each pixel value to specified threshold. If light threshold, pixels >= threshold are set to max, remaining set to min. If dark threshold, pixels <= threshold are set to max, remaining set to min.

39. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color matching

40. Transform Operations Fast Fourier Transform (FFT) Discrete Cosine Transform (DCT) Results –1D Linear –2D Linear –2D Logarithmic –Histogram Unlikely you will use transforms.

41. Types of image processing tools Assignment Arithmetic Logical Filtering Morphological Histogram Transform Color Matching

42. Executes on 3-band images. Create 1 or more filters –Specify target color as RGB or HSL –Define range in HSL coordinates Filters are applied to each pixel. Resulting image can be color or grayscale. Segments image into similar colors –Use locator or blob tool to locate instances. Be mindful of tool’s processing time.