A new parallel algorithm to compute Euclidean metric-based Hausdorff distance measures between binary images (typically edge maps) is proposed in this paper. The algorithm has a running time of
) for images of size
. Further, the algorithm has the following features: (i) simple arithmetic (ii) identical computations at each pixel and (iii) computations using a small neighborhood for each pixel. An efficient cellular architecture for implementing the proposed algorithm is presented. Results of implementation using field-programmable gate arrays show that the measures can be computed for approximately 88000 image pairs of size 128×128 in a second. This result is valuable for real-time applications like object tracking and video surveillance.