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The goal of this assignment is to extract features from the preprocessed images. This means that you reduce the number of dimensions and think of robust representations of the images.
This is step 2 of the pipeline shown in the image to the right.
You will produce a script or program called feat_extract. The arguments that
will be passed to this program are preprocessed.pgm featurefile.feat. The
first argument is an existing (preprocessed) file, which must be read. The
second argument is the file which should be written in the following format:
label 0.20 0.8 ...
where label is the class-label and each numeric value (separated by spaces)
are the feature values. Write only one line (i.e., one feature vector) per
file!
Hand in your code in a .tar.gz file, marked with your name and assignment
number. If there are compilation steps, create a Makefile, which compiles
your program with a single make command.
Your code should have a basis in the literature. Put comments in your code detailing the steps you took and on which articles you base your method.
Last modified: April 27, 2011, by Jean-Paul van Oosten
Part of the HWR course