A novel algorithm for simultaneous face detection and recognition

Face detection and recognition has been introduced in many real world applications. Several algorithms have been implemented for either detection or recognition. In this paper, a novel algorithm, which simultaneously detects and recognizes facial images employing the same method, is presented. The proposed algorithm is based on a new 2D representation for the Histogram of Oriented Gradients (2D-HOG) in conjunction with 2DPCA for feature extraction. Experimental results conducted on existing datasets, FERET, ORL, UMIST, JAFFE, and MIT-CMU, achieved better accuracy and running time compared with existing techniques.