Using MATLAB for image analysis
Image processing is generally used to optimise images so that they are either aesthetically pleasing to the human eye or we are able to get some kind of valuable information out of the images.
Instagram and snap chat filters change images- This is image processing.
We all do image processing in our everyday lives. For example, when we try to see objects that are at different distances from us, we do some unconscious image processing. Here is an exercise for you to try: Focus on a point about 10 m away from you (ie. Stare into the distance. cue harp music). Now hold your thumb up about 10 cm away from your face while continuing to focus far away. You will notice that your thumb is blurry. When you focus on your thumb, the image is sharper. You noticed that your thumb was blurry, you took actions to make it sharper. Congratulations you can image process. The brain is amazing at image processing and has developed many complex mechanisms to make sure we can function. But that is another story for another decade.
Now we've established that we are all inherently amazing image processing machines, we still need to tell our computers how to do it. Turns out that this isn't as simple. Apparently, the simpler something is for humans to do, the harder it is for computers. So while computers may be really good at doing complicated calculus, it is harder for them to identify a goat in the image below. To get our computers to identify objects in images, we need to break down the instructions into multiple simpler steps.
This course has been developed with the ultimate goal of performing simple object tracking. Apart from introducing the basics of image processing, it covers the following:
- Filters
- Image segmentation
- Making measurements on images
- Background subtraction
- Basic object tracking.
Challenge images may be found here: https://github.com/ysmohan/Using-Matlab-For-Image-Processing--Data