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Face recognition using L1 norm minimization

version 1.2 (19.2 MB) by

This code uses L1 norm minimization classifier to recognize faces.



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Read the following paper for details of the algorithm - Robust Face Recognition via Sparse Representation by John Wright, Arvind Ganesh, and Yi Ma , Coordinated Science Laboratory, University of Illinois at Urbana-Champaign and Allen Yang, Electrical Engineering and Computer Science, University of California Berkeley. The database used is MIT-CBCL and YaleB database which was got from and

Comments and Ratings (13)

efsane olmuş

hello sir i am a M-tech student and i have taken up this paper as my project.i have seen your code and is running good.i have a question regarding the code whether it is same as the Donoho concept of compressed sensing and if it is so i want to know how your code calculates the sparse coefficients.


kuanfu (view profile)

very thanks

sasikala mr

thanks dear


Islam (view profile)


Neeraj (view profile)

The low success rate is because I am doing no Preprocessing for orientation and illumination correction for this database. If you implement a good preprocessing algorithm the success rate should increase. And having used the L2 norm as a classifier for an earlier project using MIT-CBCL database personally I felt the L1 norm gives a better performance (73% to 90%).


Li (view profile)

Success rate in percentage is-(for Yale dataset)

ans =


It is too low. Is the problem the choosing of "L1 Norm Minimization"?You choose '\'.

Thank you.

raghu methre


chipo josé

thank you very match


Neeraj (view profile)

Added the databases to the package

chipo josé

Can u please give us the database

raghu methre

Can u please give us the database?



I have added the databases to the zipped package along with the code. Only the paths have to be updated and this code should work.

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