An iterative approach to region growing using associative memories

The postulate is made that ``any computation which can be performed recursively can be performed easily and efficiently by iteration coupled with association.'' The ``easily and efficiently'' part of that postulate is nontrivial to prove, and is shown by examples in this paper. The use of association leads directly to potential implementation by content-addressable memories. The example addressed is region growing, often given as a classical example of the use of recursive control structures in image processing. Recursive control structures, however, are somewhat awkward to build in hardware, where the intent is to segment an image at raster scan rates. This paper describes an algorithm and hardware structure capable of per-forming region labeling iteratively at scan rates. Every pixel is individually labeled with an identifier signifying to which region it belongs. The difficulties which often justify recursion (``U''- and ``N''-shaped regions, etc.) are handled by maintaining an equivalence table in hardware, transparent to the computer, which reads the labeled pixels. The mechanism for updating the region map is explained in detail. Furthermore, simulation of the associative memory has been demon-strated to be an effective implementation of region growing in a serial computer.