HUMAN FACE DETECTION IN COLOR IMAGES

Ihab Zaqout (), Roziati Zainuddin () and Sapian Baba ()
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Ihab Zaqout: Faculty of Computer Science & Information Technology, University of Malaya, 50603 K. L., Malaysia
Roziati Zainuddin: Faculty of Computer Science & Information Technology, University of Malaya, 50603 K. L., Malaysia
Sapian Baba: Faculty of Computer Science & Information Technology, University of Malaya, 50603 K. L., Malaysia

Advances in Complex Systems (ACS), 2004, vol. 07, issue 03n04, 369-383

Abstract: In this paper we have used a simple and efficient color-based approach to segment human skin pixels from background, using a 2D histogram-based approach as a preprocess stage for human face detection. For skin segmentation, a total of 446,007 skin samples from the training set is manually cropped from the RGB color images, to calculate three lookup tables based on the relationship between each pair of the triple components (R, G, B). Derivation of skin classifier rules from the lookup tables are based on how often each attribute value (interval) occurs, and their associated certainty values. For face detection, we assume the face-appearance as blob-like, and that the face has an approximately elliptical shape. Accordingly, an ellipse-fitting algorithm is appropriate, which is based on statistical moments, and those blobs that have an elliptical shape are retained as face candidates.

Keywords: Skin segmentation; histogram-based approach; lookup table; skin classifier; ellipse fitting; face detection; feature-based approach (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1142/S021952590400024X

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