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infinity-project.org Engineering education for today’s classroom 2 Outline How Can We Use Digital Images? A Digital Image is a Matrix Manipulating Images.

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Presentation on theme: "infinity-project.org Engineering education for today’s classroom 2 Outline How Can We Use Digital Images? A Digital Image is a Matrix Manipulating Images."— Presentation transcript:

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2 infinity-project.org Engineering education for today’s classroom 2 Outline How Can We Use Digital Images? A Digital Image is a Matrix Manipulating Images Improving Images for Robot Eyes

3 infinity-project.org Engineering education for today’s classroom 3 4.1 How Can We Use Digital Images?

4 infinity-project.org Engineering education for today’s classroom 4 The Power of Digital Images It is easier and easier to acquire or make digital images Digital cameras and scanners Chief advantage over analog (e.g. film) images: Easy to change How might we change images?

5 infinity-project.org Engineering education for today’s classroom 5 Image Softening and Blurring

6 infinity-project.org Engineering education for today’s classroom 6 Image Sharpening

7 infinity-project.org Engineering education for today’s classroom 7 Finding Edges in Images Edges in images usually define solid objects in our 3D world Finding edges is a first step to navigation and manipulation

8 infinity-project.org Engineering education for today’s classroom 8 Subtracting Images Image subtraction is a simple way to find differences between two images Useful for security, recognition, and navigation applications

9 infinity-project.org Engineering education for today’s classroom 9 Image Segmentation Segmentation: Dividing images into regions Applications Identifying foreground vs. background Finding objects using only one image

10 infinity-project.org Engineering education for today’s classroom 10 4.2 A Digital Image Is a Matrix

11 infinity-project.org Engineering education for today’s classroom 11 Digital Images are Matrices Matrix: An array of numbers A = 101134 5610 751214 3 rows and 4 columns Elements: A(i,j), i and j are integers Examples: A(2,3) = 6, A(1,4) = 7, A(3,4) = 10

12 infinity-project.org Engineering education for today’s classroom 12 Classes of Image Manipulation 1. Mapping: Pixel-by-pixel operations 2. Arithmetic Combination of Two Images: e.g. addition, multiplication 3. Filtering: Operations on groups of pixels in an image (neighborhood operation) Fact: Almost all applications are made up of simple combinations of these manipulations

13 infinity-project.org Engineering education for today’s classroom 13 Image Mapping All of the form B(i,j) = {function of A(i,j)} where B(i,j) is the output image Many familiar effects: Brightness, Contrast, Negative, Thresholding, Gamma Correction

14 infinity-project.org Engineering education for today’s classroom 14 k = -50 k = 50 Brightness Mapping B(i,j) = A(i,j) + k k = constant (expressed as a table)

15 infinity-project.org Engineering education for today’s classroom 15 Example: Brightness Mapping Original 24-bit image Each color increased by 60 Each color decreased by 60 Green and blue +60, red -60

16 infinity-project.org Engineering education for today’s classroom 16 Contrast Mapping Formula: B(i,j) = s A(i,j) If s > 1, contrast is increased If s < 1, contrast is decreased Need to quantize after multiplying, as s A(i,j) may not be an integer Aside: This setting is found on most TV sets

17 infinity-project.org Engineering education for today’s classroom 17 Contrast Mapping (cont.) s > 1 s < 1 s > 1 and k < 0 s 0

18 infinity-project.org Engineering education for today’s classroom 18 Example: Contrast and Brightness Formula: B(i,j) = s A(i,j) + k This is easy to do! Higher contrast Higher contrast with lower brightness

19 infinity-project.org Engineering education for today’s classroom 19 Example: Contrast and Brightness Given the 4-bit grayscale image A = 101134 5610 751214 Compute the image with a contrast of 1.5 and a brightness of 2

20 infinity-project.org Engineering education for today’s classroom 20 Solution: Contrast and Brightness Answer: B(i,j) = 1.5A(i,j) + 2 B = 15 78 101142 131015 Quantization causes values such as 9.5 and 3.5 to be rounded up Image is clipped at 15 (Why?)

21 infinity-project.org Engineering education for today’s classroom 21 Infinity Project Experiment – 4.1

22 infinity-project.org Engineering education for today’s classroom 22 Brightness and Contrast Grayscale

23 infinity-project.org Engineering education for today’s classroom 23 Brightness and Contrast Color Image

24 infinity-project.org Engineering education for today’s classroom 24 Brightness and Contrast Color Camera

25 infinity-project.org Engineering education for today’s classroom 25 Brightness and Contrast Cascade


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