Abstract
Human face detection is one of the most important processes in applications such as video surveillance, human computer interface, face recognition, and image database management. Algorithms have been discussed in lots of papers about face detection and face recognition. But it is well known that their implementation is not easy. Due to variations in illumination, background, visual angle and facial expressions, the problem of machine face detection is complex. Face detection algorithms have primary factors that decrease a detection ratio: variation by lighting effect, location and rotation, distance of object and complex background. We propose a face detection algorithm for color images in the presence of varying lighting conditions as well as complex background. We use the YC b C r color space since it is widely used in video compression standards and multimedia streaming services. Our method detects skin regions over the entire image, and then generates face candidate based on the spatial arrangement of the skin patches. The algorithm constructs eyes, mouth, nose, and boundary maps for verifying each face candidate.
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Kim, J.O. et al. (2004). On Extraction of Facial Features from Color Images. In: Laganá, A., Gavrilova, M.L., Kumar, V., Mun, Y., Tan, C.J.K., Gervasi, O. (eds) Computational Science and Its Applications – ICCSA 2004. ICCSA 2004. Lecture Notes in Computer Science, vol 3046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24768-5_104
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DOI: https://doi.org/10.1007/978-3-540-24768-5_104
Publisher Name: Springer, Berlin, Heidelberg
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