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

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Presentation on theme: "1 Computer Vision & Image Processing G. Andy Chang Department of Mathematics & Statistics Youngstown State University Youngstown, Ohio."— Presentation transcript:

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

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

3 CV & IP 3 Illusion (Human Vision)

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

5 CV & IP 5 Old design Wafer Human hair thickness is about 100 micron.

6 CV & IP 6 Computer Vision 564×380 Digital Image

7 CV & IP 7 2828 =256 0 ~ 255

8 CV & IP 8 Original Image (564×380) 8-bit Gray Scale Image (256 gray levels)

9 CV & IP 9 Image with 84 × 57 pixels (Low resolution)

10 CV & IP 10 3-bit Gray Scale Image (0 – 7) EXCEL WORKSHEET_AM EXCEL WORKSHEET_PM

11 CV & IP 11 Original Image (564×380) 8-bit Gray Scale Image (256 = 2 8 gray levels)

12 CV & IP 12 Smoothed Image

13 CV & IP 13 Sharpened Image

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

15 CV & IP 15 Object Identification (Binary Thresholding)

16 CV & IP 16 Object Identification

17 CV & IP 17 Object Identification

18 CV & IP 18 Object Identification

19 CV & IP 19

20 CV & IP 20

21 CV & IP 21

22 CV & IP 22

23 CV & IP 23

24 CV & IP 24

25 CV & IP 25 Old design

26 CV & IP 26 Old design

27 CV & IP 27 Oyster Size Measurement (a)(b) a) Original Image b) Binary Image of Projected Area

28 CV & IP 28 Images of Firm and Soft Apples

29 CV & IP 29 Blood Cells


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