Introduction to Computer Science – Chapter 10. CSc 2010 Spring 2011 Marco Valero. Overview. Review image basics Making pictures Image processing Shrinking and enlarging Blurring and sharpening Negative and embossing Robot vision. Image basics.
Review image basics
Shrinking and enlarging
Blurring and sharpening
Negative and embossing
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())
Height and width can be retrieved from a picture
getHeight(<pic>) and getWidth(<pic>)
We can call show(myPic, ‘my title’) to create a window with a title
Rather than taking pictures, we can create our own
width = height = 100
newPic = makePicture(width, height, black)
Each is a byte, 0-255
We can loop through each pixel just like a matrix and change the value
We can think of the bitmap as a matrix then any transformation from one picture to another is a matrix transformation
500x500 pixel bitmap
If 10 operations per transformation that’s 2.5 mil ops!
Image processing is is intensive
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]
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])
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)
Are computers good at recognizing objects?
Are _we_ good at recognizing objects?
What would a simple tracking code look like?
What if we only focused on the object?
We can use high contrast filter
What are the issues with this?
Compare to older program