Introduction to Computer Science – Chapter 9

1. Introduction to Computer Science – Chapter 9 CSc 2010 Spring 2011 Marco Valero

2. Overview • Review image basics • Making pictures • Image processing • Shrinking and enlarging • Blurring and sharpening • Negative and embossing • Robot vision

3. Image basics • We used takePicture and show to respectively take and show pictures already • We’ve also seen savePicture as a means to save a snapshot to disk • makePicture(<filename>) will load a picture from disk and return a picture object • myPic = makePicture(pickAFile())

4. Image basics • Height and width can be retrieved from a picture • getHeight(<pic>) and getWidth(<pic>) • show(<pic>,<title>) • We can call show(myPic, ‘my title’) to create a window with a title

5. Making pictures • Rather than taking pictures, we can create our own • width = height = 100 • newPic = makePicture(width, height, black) • RGB • Each is a byte, 0-255 • We can loop through each pixel just like a matrix and change the value

6. Image processing • We can think of the bitmap as a matrix then any transformation from one picture to another is a matrix transformation • 500x500 pixel bitmap • 250k pixels • If 10 operations per transformation that’s 2.5 mil ops! • Image processing is intensive

7. Shrinking & enlarging • If we wanted to shrink a given n x n image by a factor of f • Result size is n/f x n/f • Bitmap[x*f, y*f] -> NewBitmap[x, y] • Enlarging is the inverse • Result size is n*f x n*f • Bitmap[x/f, y/f] -> NewBitmap[x, y]

8. Blurring & sharpening • Pixel transformation as a result of its local neighbors’ values • Blurring is done by setting a pixels value to the averages of its neighbors • V = sum([getRed(up),getRed(left),…]) / 5 • Sharpening is done by subtracting the sum of its neighbors • V = 5*getRed(self) – sum([neighborvalues])

9. Negative & embossing • To create a negative of an image we simply subtract 255 from the current value • V = 255 – getRed(pixel) • Creating an embossed effect is done by subtracting a neighbors value from a pixel • V = getRed(pixel) – getRed(neighbor)

10. Robot vision • Are computers good at recognizing objects? • Are _we_ good at recognizing objects? • What would a simple tracking code look like?

11. Robot vision • What if we only focused on the object? • We can use high contrast filter • What are the issues with this? • Blob filtering • takePicture(‘blob’) • Compare to older program