A basic object recognition system was developed using Fourier descriptors and minimum-distance classification from a stored object template using MATLAB. The essential idea was to represent the coordinates as complex numbers for computing the Fourier descriptors of the image, then reduce the descriptors using a low-pass filter which will remove the high-frequency content (ie, the detail) and keep the basic shape. The basic shape could then be compared to stored templates and classified using, in this case, a minimum distance classifier. Cody developed the system independently as part of an image processing class. Presentation slides are below.
Unfortunately, I’ve misplaced the source code and experimental results for this system. (I believe they were lost due to an unfortunate orange juice laptop incident, but might be on a school computer.)
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