Abstract: Foreground/background segmentation is a technique that shares the same goals of Blue-screen chroma keying  to separate the foreground from the background  but does so without the strong requirement of the existence of a known screen behind the subject of interest. Instead, a model of the background is built using historic and weak prior knowledge. Because of the computation-intensive nature of model-based segmentation algorithms, foreground/background segmentation at video rates is a challenging problem without the use of custom hardware or high-end workstations. We discuss techniques used in the implementation of a real-time foreground/background segmentation algorithm on a general-purpose consumer grade PC. In particular we demonstrate optimization techniques in the implementation of three critical sections of our algorithm: Binary Morphological Filter, Directional Morphological Filter and Region Flood Fill. These techniques exploit the instruction set of the Pentium®II and Pentium®III processors allowing video
segmentation of 320x240 color frames at 25 fps. The optimized critical sections may be immediately used in a plethora of other applications. Moreover, the optimization methodology provides useful insight into the optimization of other image processing and computer vision techniques, such as edge detection, object boundary localization, and morphological pre- and post-processing.