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Mathematics in Everyday Life Gilad Lerman Department of Mathematics University of Minnesota ighland park elementary (6 th graders)

Mathematics in Everyday Life.ppt

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Page 1: Mathematics in Everyday Life.ppt

Mathematics in Everyday Life

Gilad LermanDepartment of Mathematics

University of Minnesota

Highland park elementary (6th graders)

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What do mathematicians do?What homework do I give my students?

• Example of a recent homework: Denoising

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What do mathematicians do?What projects do I assign my students?

• Example of a recent project: Recognizing Panoramas • Panorama:

• How to obtain a panorama?

wide view of a physical space

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How to obtain a panorama

1. By “rotating line camera”2. Stitching together multiple images Your camera can do it this way… E.g. PhotoStitch (Canon PowerShot SD600)

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Experiment with PhotoStitch

Experiment done by Rebecca Szarkowski

Input: 10 images along a bridge

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Experiment continued…

Experiment done by Rebecca Szarkowski

Output: Panorama (PhotoStitch)

Output: Panorama (by a more careful mathematical algorithm)

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What’s math got to do with it?

From visual images to numbers (or digital images)

New Topic: Relation of Imaging and Mathematics

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Digital Image Acquisition

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From Numbers to ImagesLet us type the following numbers

1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8

We then color them so 1=black, 8=white rest of colors are in between

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One more time…Now we’ll try the following numbers

1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 8 8 8 8 8 8 8 8 16 16 16 16 16 16 16 16 32 32 32 32 32 32 32 32 64 64 64 64 64 64 64 64128 128 128 128 128 128 128 128

We then color them so 1=black, 128=white rest of colors are in between

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Let’s compare 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6 6 6 7 7 7 7 7 7 7 7 8 8 8 8 8 8 8 8

1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 4 4 4 4 4 4 4 4 8 8 8 8 8 8 8 8 16 16 16 16 16 16 16 16 32 32 32 32 32 32 32 32 64 64 64 64 64 64 64 64128 128 128 128 128 128 128 128

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From an Image to Its NumbersWe start with clown imageIt has 200*320 numbersI can’t show you all…Let’s zoom on eye (~40*50)

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Image to Numbers (Continued)We’ll zoom on middle of eye image (10*10)

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The Numbers (Continued)The middle of eye image (10*10)

80 81 80 80 80 80 77 77 37 11 81 80 81 80 80 80 77 37 9 6 80 80 80 80 80 80 37 11 2 11 80 80 80 80 80 77 66 66 66 54 80 80 80 80 77 77 77 80 77 80 80 80 79 77 66 54 66 77 66 54 77 80 77 70 22 57 51 70 51 70 77 73 70 22 2 2 22 37 37 22 77 77 54 37 1 6 2 8 2 6 77 70 70 22 2 2 6 8 8 6

Note the rule: Bright colors – high numbers Dark colors - low numbers

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More Relation of Imaging and Math

Averaging numbers smoothing imagesIdea of averaging: take an imageReplace each point by average with its neighbors

For example, 2 has the neighborhood

So replace 2 by

80 81 80 80 80 80 77 77 37 11 81 80 81 80 80 80 77 37 9 6 80 80 80 80 80 80 37 11 2 11 80 80 80 80 80 77 66 66 66 54 80 80 80 80 77 77 77 80 77 80 80 80 79 77 66 54 66 77 66 54 77 80 77 70 22 57 51 70 51 70 77 73 70 22 2 2 22 37 37 22 77 77 54 37 1 6 2 8 2 6 77 70 70 22 2 2 6 8 8 6

70 22 57 22 2 2 37 1 6

80 81 80 80 80 80 77 77 37 11 81 80 81 80 80 80 77 37 9 6 80 80 80 80 80 80 37 11 2 11 80 80 80 80 80 77 66 66 66 54 80 80 80 80 77 77 77 80 77 80 80 80 79 77 66 54 66 77 66 54 77 80 77 70 22 57 51 70 51 70 77 73 70 22 2 2 22 37 37 22 77 77 54 37 1 6 2 8 2 6 77 70 70 22 2 2 6 8 8 6

70+22+57+22+2+2+37+1+6 1249 3

=

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Example: Smoothing by averaging

Original image on top left It is then averaged with neighborsof distances 3, 5, 19, 15, 35, 45

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Example: Smoothing by averaging

And removing wrinkles by both….

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More Relation of Imaging and Math

Differences of numbers sharpening images

On left image of moonOn right its edges (obtained by differences)We can add the two to get a sharpened version of the first

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Moon sharpening (continued)

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Real Life Applications

• Many…• From a Minnesota based company…

• Their main job: maintaining railroads• Main concern: Identify cracks in railroads, before too late…

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How to detect damaged rails?• Traditionally… drive along the rail (very long) and

inspect • Very easy to miss defects (falling asleep…)• New technology: getting pictures of rails

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Millions of images then collected

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How to detect Cracks?

• Human observation…• Train a computer… • Recall that differences detect edges…

Work done by Kyle Heuton (high school student at Saint Paul)

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Summary

• Math is useful (beyond the grocery store)• Images are composed of numbers• Good math ideas good image processing