There is a continual need for faster and accurate stereo vision algorithms. While scan-line based algorithms are fast they
are less accurate and algorithms based on probabilistic models are accurate but more time consuming. In this work, a
new scan-line based algorithm that defines feature fronts according to the level set method is introduced. The feature
fronts are matched using a new matching criterion that also compares the feature strengths in addition to an end-point
SAD score. Feature fronts are sorted based on their strengths and strongest fronts are matched first. The algorithm seeks
to identify visible fronts where a front is defined to be visible if it turns out to be its match's match. Continuity of feature
fronts is imposed by requiring neighboring feature fronts in one image match to neighboring feature fronts in the other
image or to no front.