Parallel Algorithms for Arbitrary Dimensional Euclidean Distance Transforms With Applications on Arrays With Reconfigurable Optical Buses

2004 ◽  
Vol 34 (1) ◽  
pp. 517-532 ◽  
Author(s):  
Y.-R. Wang ◽  
S.-J. Horng
Keyword(s):  
Parallel Algorithms ◽  
Euclidean Distance ◽  
Distance Transforms ◽  
Optical Buses

scholarly journals N-D Linear Time Exact Signed Euclidean Distance Transform

2003 ◽  
Author(s):  
Nicholas J. Tustison ◽  
Marcelo Siqueira ◽  
James Gee
Keyword(s):  
Computer Vision ◽  
Euclidean Distance ◽  
Linear Time ◽  
Small Time ◽  
Direct Application ◽  
Distance Transform ◽  
Fast Computation ◽  
Distance Transforms ◽  
Euclidean Distance Transform ◽  
Image Pixels

Fast computation of distance transforms find direct application in various computer vision problems. Currently there exists two image filters in the ITK library which can be used to generate distance maps. Unfortunately, these filters produce only approximations to the Euclidean Distance Transform (EDT). We introduce into the ITK library a third EDT filter which was developed by Maurer {} . In contrast to other algorithms, this algorithm produces the exact signed squared EDT using integer arithmetic. The complexity, which is formally verified, is O(n) O(n) with a small time constant where n n is the number of image pixels.

DATA PARALLEL COMPUTATION OF EUCLIDEAN DISTANCE TRANSFORMS

1992 ◽  
Vol 02 (04) ◽  
pp. 331-339 ◽  
Author(s):  
TERRY BOSSOMAIER ◽  
NATALINA ISIDORO ◽  
ADRIAN LOEFF
Keyword(s):  
High Speed ◽  
Euclidean Distance ◽  
Maximum Error ◽  
Parallel Computers ◽  
Data Sets ◽  
Data Parallel ◽  
Distance Transforms ◽  
Diverse Data ◽  
Mimd Architectures ◽  
New Strategies

The Euclidean Distance Transform is an important, but computationally expensive, technique of computational geometry, with applications in many areas including image processing, graphics and pattern recognition. Since the data sets used are typically large, one might hope that parallel computers would be suitable for its determination. We show that existing parallel algorithms perform poorly on certain data sets and introduce new strategies. These achieve high speed on diverse data sets, but fail occasionally in pathological cases. We determine the maximum error in such cases and demonstrate that it is satisfactorily low. Although adequate efficiency is achievable on SIMD machines, we demonstrate that problems of this kind are data parallel yet best suited to MIMD architectures.

ON DESIGNING COMMUNICATION-INTENSIVE ALGORITHMS FOR A SPANNING OPTICAL BUS BASED ARRAY

1995 ◽  
Vol 05 (03) ◽  
pp. 499-511 ◽  
Author(s):  
CHUNMING QIAO
Keyword(s):  
Parallel Algorithms ◽  
Parallel Implementation ◽  
Reconfigurable Array ◽  
The Matrix ◽  
Matrix Transposition ◽  
Optical Buses ◽  
And Control

The Reconfigurable Array with Spanning Optical Buses (or RASOB) architecture provides flexible reconfiguration and strong connectivities with low hardware and control complexities. We use a parallel implementation of the matrix transposition as well as multiplication algorithms as an example to show how the architectural capabilities can be taken advantage of in designing efficient parallel algorithms.

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