Face localization based on the morphological multiscale fingerprints

Abstract Face localization is a previous step for face recognition systems. We propose morphological multiscale fingerprints (MMF) as a holistic feature extraction technique for face localization. The MMF is computed as the local maxima and minima preserved up to a certain scale in a multiscale analysis based on morphological erosion and dilation. We do not consider any geometrical model of the face features. As an initial validation of our approach, we have compared it with principal component analysis (PCA) over a small custom image database. Afterwards, we have tested it over the CMU image database, with good results. Finally, we present the receiving operator curve (ROC) results as well as some instances of face detection.

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