Coded targets are artificially created and usually visually distinct objects.
They are introduced in an enviroment to convey information for visual interpretation (i.e. in image form).
One of the simplest forms of coded targets are the EAN-codes found on most price tags in grocery stores of today.
More advanced coded targets are often used in VR and augmented reality applications to convey localization clues
(just like the room numbers in the MIT buildings lab corridors) in a visibly interpretable way.
In addition, color is one of the most powerful descriptors that are available in image processing and can be used
for coded targets as well.
Full color image processing methods are often easy to use and can be very efficient tools in object segmentation.
Your solution should be robust enough to be able to correctly classify at least 90% of the supplied images correctly and at the same be general enough to correctly classify at least 80% of the (hidden) grading data set.
Present your solution in a written report, complete with source code and
some examples of segmented images.
Your sourcecode should also be available in binary form on your CS UNIX account under the path
~username/edu/ia/lab2/
Note:
On your reports front page you should include
Make sure you include a detailed section in the report where you evaluate
the assigment, it's difficulty level (data set by data set),
your solution, your solutions performance and run-time efficiensy etc.
Also note: As there are some compatibility issues between UNIX matlab and Windows matlab: make sure your code is runnable on Matlab for Windows.
Be prepared to present and defend your work verbally.
This assignment is to be carried out individually.
Your solution must conform to the following architecture in order to be graded: Your solution may have many parts but should be callable in matlab as
nr = lab2a(image from dataset)
where nr
is an integer containing the number of post-its found in the image.
(The exact parameter format should be as in the provided procedure stubs)
Program stub lab2a.m and database public1.zip
Hints:
The matlab function bwlabel
will most likely be useful when you are counting objects
All post-its to be counted are grouped close to each other, but none of them overlap