A rough fuzzy neural network approach for robust face detection and tracking - Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition - page 247

4.1 Skin Map Segmentation Results
Several experiments were performed on real images to test the efficacy of the proposed meth-
od. In Figures 6 and 7 , we present the results obtained by applying this method to some im-
ages.
FIGURE 6 Images of CalTech, IMM, and CMU face database and skin map obtained by the
algorithm proposed.
FIGURE 7 Multiface image and the skin map obtained by the algorithm proposed.
5 Face detection
Face detection is achieved by detecting elliptical regions in the skin map by properly modify-
ing the Orientation Matching (OM) technique reported in Ref. [ 32 ] . The technique detects cir-
cular objects of radius in the interval [ r m , r M ], computing the OM transform of the input image
and taking the peaks of the transform, which correspond to the centers of the circular patterns.
To customize the technique for handling our problem of detecting elliptical patern in the skin
map, we performed a statistical analysis on 500 images taken from the databases used to test
the method to find a proper ratio between major and minor semi-axis of ellipses around faces.
We statistically found this ratio as 0.75. In Figures 8 and 9 , we present the results achieved by
applying this method to the binary skin map obtained as the output of the multiscale method.
FIGURE 8 Images of CalTech, IMM, and CMU face database and the results of the OM tech-
nique.
FIGURE 9 Multiface image and the result of the OM technique.