### Abstract

A distance transform converts a binary image consisting of foreground (feature) and background (nonfeature) elements into a gray level image, where each element contains the distance from the corresponding element to the nearest foreground element. The calculation of exact Euclidean distance transform is a computationally intensive task and, therefore, approximations are often utilized. These algorithms are typically iterative or require several passes to complete the transform. In this paper, a novel parallel single-pass algorithm for the calculation of constrained distance transform is presented. The algorithm can be implemented by utilizing only bit-wise logical operations; thus, it is well suited for low-cost bit-serial SIMD architectures or conventional uniprocessors with a large word width, where the SIMD operation is emulated. Implementations on a parallel SIMD architecture and a sequential architecture are described. Comparisons are provided, showing results of the implementations of the presented algorithm, a sequential local algorithm utilizing integer approximated distances and an algorithm utilizing exact Euclidean distances.

Original language | English |
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Pages (from-to) | 150-161 |

Journal | Computer Vision and Image Understanding |

Volume | 74 |

Issue number | 2 |

DOIs | |

Publication status | Published - 1999 |

MoE publication type | A1 Journal article-refereed |

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## Cite this

Takala, J., & Viitanen, J. (1999). Distance transform algorithm for bit-serial SIMD architectures.

*Computer Vision and Image Understanding*,*74*(2), 150-161. https://doi.org/10.1006/cviu.1999.0756