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A new generic scheme for incremental implementations of distance transforms (DT) is presented: Incremental Distance Transforms (IDT). This scheme is applied on the city-block, Chamfer, and three recent exact Euclidean DT (E 2 DT). A benchmark shows that for all five DT, the incremental implementation results in a significant speedup: 3.4 × -10×. However, significant differences (i.e., up to 12.5×) among the DT remain present. The FEED transform, one of the recent E 2 DT, even showed to be faster than both city-block and Chamfer DT. So, through a very efficient incremental processing scheme for DT, a relief is found for E 2 DT's computational burden.
Schouten et al. (Sun,) studied this question.