Comparative analysis of simple facial features extractors
In the article a certain class of feature extractors for face recognition is presented. The extraction is based on simple approaches: image scaling with pixel concatenation into a feature vector, selection of a small number of points from the face area, face images spectrum, and finally pixel intensities histogram. The experiments performed on several facial image databases (BioID [4], ORL face database [27], FERET [30]) show that face recognition using this class of extractors is particularly efficient and fast, and can have straightforward implementations in software and hardware systems. They can also be used in fast face recognition system involving feature-integration, as well as a tool for similar faces retrieval in 2-tier systems (as initial processing, before exact face recognition).
face recognition histogram face retrieval feature extraction dct dft