  We present a simple solution for segmenting grayscale images using existing
Connected Component Labeling (CCL) algorithms (which are generally applied to
binary images), which was efficient enough to be implemented in a constrained
(embedded automotive) architecture. Our solution customizes the region growing
and merging approach, and is primarily targeted for stereoscopic disparity
images where nearer objects carry more relevance. We provide results from a
standard OpenCV implementation for some basic cases and an image from the
Tsukuba stereo-pair dataset.
