Video and Image Processing Blockset 2.8

Color Segmentation

This demo tracks a person's face and hand using a color-based segmentation method.

Contents

Demo Model

The following figure shows the Color Segmentation demo model:

Color Segmentation Results

To create an accurate color model for the demo, many images containing skin color samples were processed to compute the mean (m) and covariance (C) of the Cb and Cr color channels. Using this color model, the Color Segmentation/Color Classifier subsystem classifies each pixel as either skin or nonskin by computing the square of the Mahalanobis distance and comparing it to a threshold. The equation for the Mahalanobis distance is shown below:

SquaredDistance(Cb,Cr) = (x-m)'*inv(C)*(x-m), where x=[Cb; Cr]

The result of this process is binary image, where pixel values equal to 1 indicate potential skin color locations.

The Color Segmentation/Filtering subsystem filters and performs morphological operations on each binary image, which creates the refined binary images shown in the Skin Region window.

The Color Segmentation/Region Filtering subsystem uses the Blob Analysis block and the Extract Face and Hand subsystem to determine the location of the person's face and hand in each binary image. The Display Results/Mark Image subsystem uses this location information to draw bounding boxes around these regions.

Available Demo Versions

Windows® only: vipcolorsegmentation_win.mdl

Platform independent: vipcolorsegmentation_all.mdl

Windows-only demo models might contain compressed multimedia files or To Video Display blocks, both of which are only supported on Windows platforms. The To Video Display block supports code generation, and its performance is optimized for Windows.