Alignment-free sparse representation based classification method via fast location

This paper aims at optimizing the efficiency of the sparse representation based classification (SRC) method in automatic recognition, which is a common problem with large quantity of sample images. An automated target recognition framework based on SRC method is proposed through fast locating to the region of interest (ROI) and dictionary filtering meanwhile. We solve the alignment problem through the fast locating and get an alignment-free SRC method for different poses of a 3D target. We propose two methods for the fast locating in the paper. The dictionary filtering is done according to the probe image. The proposed method has been operated on car and face databases. Car recognition aiming at multi-pose recognition, a car-model database is set up, and its capturing equipment and environments are introduced. On this database, the performance of the proposed method is assessed and compared with the original SRC method. Then, we have further performed the method on yawl B database for face recognition. Then we conclude that the proposed method improves the efficiency and accuracy of the original SRC method.