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Computer Vision & Image Processing

Computer Vision & Image Processing. G. Andy Chang Department of Mathematics & Statistics Youngstown State University Youngstown, Ohio. Human Vision. Illusion. 1. Green > Red 2. Green = Red 3. Green < Red. Illusion (Human Vision). Vision System. Human Vision Qualitative

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Computer Vision & Image Processing

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  1. Computer Vision & Image Processing G. Andy Chang Department of Mathematics & Statistics Youngstown State University Youngstown, Ohio

  2. Human Vision Illusion 1. Green > Red 2. Green = Red 3. Green < Red

  3. Illusion (Human Vision)

  4. Vision System Human Vision • Qualitative • Comparative Computer Vision • Quantitative • 320 pixels • 334 pixels Pixel (combination of Picture & Element) is the smallest element of a display which can be assigned a color.

  5. Old design Wafer • Human hair thickness is about 100 micron.

  6. Computer Vision 564×380 Digital Image

  7. 28 =256 0 ~ 255

  8. Original Image (564×380)8-bit Gray Scale Image (256 gray levels)

  9. Image with 84 × 57 pixels(Low resolution)

  10. 3-bit Gray Scale Image (0 – 7) EXCEL WORKSHEET_AM EXCEL WORKSHEET_PM

  11. Original Image (564×380)8-bit Gray Scale Image (256 = 28 gray levels)

  12. Smoothed Image

  13. Sharpened Image

  14. Inverted Image (564×380)8-bit Gray Scale Image 0  255 1  254 2  253 3  252 4  251 5  250 …

  15. Object Identification (Binary Thresholding)

  16. Object Identification

  17. Object Identification

  18. Object Identification

  19. Old design

  20. Old design

  21. Oyster Size Measurement (a) (b) a) Original Image b) Binary Image of Projected Area

  22. Images of Firm and Soft Apples

  23. Blood Cells

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