PARALLEL SPLIT-LEVEL RELAXATION
Ashok K. Samal, Tom Henderson · International Journal of Pattern Recognition and Artificial Intelligence · 1988
The goal of high level vision is to identify a set of regions in a given image. This has been called by various names: the scene labeling problem’, the consistent labeling problem2, the constraint satisfaction problem3, Waltz filtering4, the satisfying assignment problem5, etc. There are several approaches to solve this problem, including backtracking, graph matching and relaxation. A new method called split-level relaxation, which is based on discrete relaxation was proposed in Ref. 6. It takes care of multiple semantic constraints by considering each of them independently. The problem is known to be NP-complete, so it takes a long time to solve. With the advent of multiprocessors, it is now imperative to see if the problem can be solved faster in the average case. In this paper we give a framework for solving the scene analysis problem in a parallel processing environment, using split-level relaxation. Experiments done on a multiprocessor show that it is indeed advantageous to use multiprocessors to solve this problem.