Abstract
Automatic face and landmarks detection on images is very important for face recognition. In this paper, we present an approach for detecting face and facial features such as eyes, nose and mouth in gray scale images. We make use of thresholding and connected component labelling algorithm to detect a face and extract features that characterize this face. This approach has the advantage that no manual interaction is required for choosing and extracting components. Experiments show promising results for face images having different orientation and facial expression.
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Momin, H., Tapamo, JR. (2011). Automatic Detection of Face and Facial Landmarks for Face Recognition. In: Kim, Th., Adeli, H., Ramos, C., Kang, BH. (eds) Signal Processing, Image Processing and Pattern Recognition. SIP 2011. Communications in Computer and Information Science, vol 260. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27183-0_26
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DOI: https://doi.org/10.1007/978-3-642-27183-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27182-3
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