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Pixel-based skin color detection technique

Zaqout I., Zainuddin R., Baba S.

Machine Graphics and Vision

2005

Vol. 14, No. 1

61-70

One of the simplest features used for the human face detection problem is the skin color information. A simple and relatively efficient histogram-based algorithm to segment skin pixels from a complex background is presented. The histogram-based algorithm used here is referred to as the lookup table (LUT) and is adopted to identify those intervals which may fall in the skin locus plane. For that purpose, a total of 306,401 skin samples are manually collected from RGB color images to calculate three lookup tables based on the relationship between each single pair of the three components (R, G, B). To estimate the skin locus boundary, a skin classifier box is created by integration of the proposed three heuristic rules based on how often each RGB pixel-relationship falls into its interval.

A feature-based approach for segmenting faces

Zaqout I., Zainuddin R., Baba S.

Machine Graphics and Vision

2004

Vol. 13, No. 3

249-259

Human face detection has always been an important problem for face, expression and gesture recognition. Though numerous attempts have been made to detect and localize faces, these approaches have made assumptions that restrict their extension to more general cases. We identify that the key factor in a generic and robust system is that of using a large amount of image evidence, related and reinforced by model knowledge through a probabilistic framework. In this paper, we propose a feature-based algorithm for segmenting faces that is sufficiently generic and is also easily extensible to cope with more demanding variations of the imaging conditions. The algorithm detects feature points from the image and groups them into face candidates using geometric and grey level constraints. Preliminary results are provided to support the validity of the approach and demonstrate its capability to segment faces under different scales, orientations and viewpoints.