Feature Extraction Based on Nearest Feature Line and Compressive Sensing
Lijun Yan, Jeng‐Shyang Pan, Xiaorui Zhu · 2013
In this paper, a novel feature extraction algorithmbased on nearest feature line and compressive sensing is proposed.The prototype samples are transformed to compressivesensing domain and then are performed Neighborhood discriminantnearest feature line analysis (NDNFLA) in the proposedalgorithm. This method can reduce the computational complexityfor feature extraction using nearest feature line. At the same time.its average recognition rate is very close to that of NDNFLA. Theproposed algorithm is applied to image classification on AR faceDatabase. The experimental results demonstrate the effectivenessof the proposed algorithm