๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Distance Transform Algorithm for Bit-Serial SIMD Architectures

โœ Scribed by Jarmo H Takala; Jouko O Viitanen


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
172 KB
Volume
74
Category
Article
ISSN
1077-3142

No coin nor oath required. For personal study only.

โœฆ Synopsis


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 singlepass 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.


๐Ÿ“œ SIMILAR VOLUMES


Structure-from-motion algorithms for com
โœ B.F. Buxton; D.W. Murray; H. Buxton; N.S. Williams ๐Ÿ“‚ Article ๐Ÿ“… 1985 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 839 KB

Algorithms for interpreting the motion of edge features in an image sequence in terms of the position, orientation and motion of a planar visible surface facet have been developed and implemented on an SIMD processor array. The underlying theory of the interpretation based on a simultaneous solution

Constant-Time Algorithm for the Euclidea
โœ Amitava Datta; Subbiah Soundaralakshmi ๐Ÿ“‚ Article ๐Ÿ“… 2001 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 288 KB

The Euclidean distance transform (EDT) is an operation to convert a binary image consisting of black and white pixels to a representation where each pixel has the Euclidean distance of the nearest black pixel. The EDT has many applications in computer vision and image processing. In this paper, we p