Parallel search for the interpretation of aerial images

Abstract

In this paper, we present a parallel search scheme for model-based interpretation of aerial images, following a focus-of-attention paradigm. Interpretation is performed using the gray level image of an aerial scene and its segmentation into connected components of almost constant gray level. Candidate objects are generated from the window as connected combinations of its components. Each candidate is matched against the model by checking if the model constraints are satisfied by the parameters computed from the region. The problem of candidate generation and matching is posed as searching in the space of combinations of connected components in the image, with finding an (optimally) successful region as the goal. Our implementation exploits parallelism at multiple levels by parallelizing the management of the open list and other control tasks as well as the task of model matching. We discuss and present the implementation of the interpretation system on a Connection Machine CM-2. The implementation reported a successful match in a few hundred milliseconds whenever they existed.