We present a new approach to the segmentation problem by optimizing a criterion which estimates the quality of a segmentation. Our method offers a general framework for solving a large class of segmentation problem. We use a graph-based description of a partition of an image and a merging strategy based on the optimal use of a sequence of criteria. An efficient data structure enables our implementation to have a low algorithmic complexity. We show how we adapt this method to segment 2-d natural images including color images and how we use results for solving the stereo matching problem.
Olivier Monga, Olivier Monga,
"A New Segmentation Method And Its Application To Stereo Vision", Proc. SPIE 0786, Applications of Artificial Intelligence V, (11 May 1987); doi: 10.1117/12.940669; https://doi.org/10.1117/12.940669