Robust Face Recognition Based on Sparse Coding with MATLAB Implementation

In this article, I present a highly practical and robust MATLAB implementation for face recognition utilizing sparse coding methodology. This program is developed based on Mr. Yang's foundational research paper and serves as an excellent resource for beginners to systematically grasp sparse coding principles and their practical applications. The implementation employs sparse representation classification (SRC) algorithm with robust error handling, where facial images are represented as linear combinations of dictionary atoms with sparse coefficients. Notably, the system demonstrates exceptional recognition accuracy for both occluded and non-occluded facial images through its l1-minimization optimization approach and residual calculation mechanism. Through hands-on experience with this code, you will gain deeper insights into sparse coding fundamentals, including dictionary learning, sparse optimization techniques, and classification decision mechanisms, ultimately enhancing your proficiency in face recognition applications.