A Feature-Based Face Recognition Approach Using Gabor Wavelet Filters Cascaded with Concurrent Neural Modules

摘要

We propose a face recognition model consisting of the following stages: facial feature localization (23 essential points, corresponding to eyes, mouth, nose, and face boundary); feature representation by Gabor Wavelet based Filtering (GWF); dimensionality reduction using Principal Component Analysis (PCA); neural classification using Concurrent Self-Organizing Maps (CSOM). For the ORL face database, we obtain a recognition score of 96%.