Work

A General Algorithm for Computing Distance Transforms in Linear Time

Year: 2005

Type: book-chapter

Abstract: A new general algorithm for computing distance transforms of digital images is presented. The algorithm consists of two phases. Both phases consist of two scans, a forward and a backward scan. The first phase scans the image column-wise, while the second phase scans the image row-wise. Since the computation per row (column) is independent of the computation of other rows (columns), the algorithm can be easily parallelized on shared memory computers. The algorithm can be used for the computation of the exact Euclidean, Manhattan (L 1 norm), and chessboard distance (L ∞ norm) transforms.

Source: Kluwer Academic Publishers eBooks

DOI: 10.1007/0-306-47025-x_36

Authors: A. Meijster, J. B. T. M. Roerdink, W. H. Hesselink

Institution: University of Groningen

Language: English

Topic: Digital Image Processing Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1517229131

FWCI: 18.25

Cites: 6

Cited by: 245

Related to: 10