Vision implies objects, so a vision system front-end needs to produce a feature-based description of image objects. The functional boundaries and specifications for the front-end are derived from analyzing: 1) What feature information can be extracted from context-free video? 2) What feature information will reduce the probability distribution model complexity for statistical object recognition and tracking? 3) How should the feature information be encoded? Segmentation is a flexible tool for extracting features. Recently proposed segmentation algorithms can be adapted to high-performance, low-cost hardware. Inexpensive segmentation will have a multiplying affect on vision system performance/complexity. Two examples are techniques for extending hardware functions into both parallel pixel processes and object tracking.