A systolic algorithm for Euclidean distance transform
Miyuki Miyazawa, Peifeng Zeng, Naoki Iso, Toshiaki Hirata · IEEE Transactions on Pattern Analysis and Machine Intelligence · 2006
The Euclidean distance transform is one of the fundamental operations in image processing. It has been widely used in computer vision, pattern recognition, morphological filtering, and robotics. This paper proposes a systolic algorithm that computes the Euclidean distance map of an N x N binary image in 3N clocks on 2N(2) processing cells. The algorithm is designed so that the hardware resources are reduced; especially no mulitipliers are used and, thus, it facilitates VLSI implementation.