Approximating Euclidean distance transform with simple operations in cellular processor arrays

This paper presents a new algorithm for computing a distance transform, particularly suitable for massively parallel cellular processor arrays. The proposed Enhanced City Block Distance Transform (ECBDT) achieves good approximation to Euclidean distances, operating with 'increment' and 'minimum' operations only, and requiring only local 4-neighbour communication. The distance values are calculated in a wave-propagating manner, and are suitable for implementation on asynchronous processor arrays. The performance of the algorithm is adjustable through parameters. Presented simulation results illustrate the operation of the algorithm, and discuss the accuracy of the distance approximation that is achieved in comparison to Euclidean, City Block, Chessboard and Chamfer distance transforms.