Principal Component Analysis for handwritten digit recognition

Loïc Abbès and I chose to work on handwritten character recognition for our term project. It was supervised by Laurence Likforman. Actually, we focused on the Most Significant Component Analysis, which preceeds the actual character classification.

Link	Size	Description
	264 kB	Our report (in French) January 2005 update: this is a reworked version of the initial report (same content, with a few corrections and improved presentation).
	8 kB	Compressed archive that gathers our whole work, including our programs (in Matlab), the generated images, our presentation (PowerPoint) and our report (along with its LaTeX sources). January 2005 update: unfortunately the archive was lost! But I could recuperate the original report and reconstitute the scripts from its content. In the process, I converted the Matlab script in Octave scripts. This archive contains the Octave scripts and the LaTeX source of the report.
	8 MB	The digits used in this project. The data was published by NIST, more data, and their format, are available.
	28 kB	The labels corresponding to the digits used in this project.