Final Results

After a long delay, we are proud to announce that we succeeded in our project. We achieved 90% accuracy in character recognition (using Chen's method), a big accomplishment. Because we did not rectify our images (undistort them), the shapes were skewed. We got 74% accuracy on shapes.

As a comparison to the much simpler Hu moments, Chen's method improved letter recognition by a significant 25 percentage points (65% vs 90%). Shape recognition was unchanged.

Our final report is here: http://cseweb.ucsd.edu/classes/wi10/cse190-a/reports/wgrant_lkander.pdf

We may post the matlab code for Chen's method, which involved radon transforms, dual-tree complex wavelet transforms, and fourier transforms, as well as k-means clustering for image segmentation.

Any questions, just send a message.

Also, we got an A. :)