Feature Extraction Based on Nearest Feature Line and Compressive Sensing

Abstract

In this paper, a novel feature extraction algorithm based on nearest feature line and compressive sensing is proposed. The prototype samples are transformed to compressive sensing domain and then are performed Neighborhood discriminant nearest feature line analysis (NDNFLA) in the proposed algorithm. This method can reduce the computational complexity for feature extraction using nearest feature line. At the same time.its average recognition rate is very close to that of NDNFLA. The proposed algorithm is applied to image classification on AR face Database. The experimental results demonstrate the effectiveness of the proposed algorithm.