Breadth-first search and its application to image processing problems

This paper explores the use of breadth-first graph traversal for the processing of digital images. It presents efficient algorithms for eroding, dilating, skeletonizing, and distance-transforming regions. These algorithms work by traversing regions in a breadth-first manner, using a queue for storage of unprocessed pixels. They use memory efficiently—pixels are removed from the queue as soon as their processing has been completed—and they process only pixels in the region (and their neighbors), rather than requiring a complete scan of the image. The image is still represented as a pixel matrix in memory; the graph is just a convenient framework for thinking about the algorithms.