Proceedings Article10.1109/SPDP.1994.346172
Distributed image edge detection methods and performance
Xiaodong Zhang,Hong Deng +1 more
- 26 Oct 1994
- pp 136-143
15
TL;DR: This paper presents the experience with parallelizing an edge detection application algorithm that reduces noise and unnecessary detail in a gray-scale image from a coarse level to a fine level of resolution by using an edge focusing technique.
read more
Abstract: An edge detection process in computer vision and image processing detects any types of significant features appearing as discontinuities in intensities. This paper presents our experience with parallelizing an edge detection application algorithm that reduces noise and unnecessary detail in a gray-scale image from a coarse level to a fine level of resolution by using an edge focusing technique. Numerical methods and parallel implementations of edge focusing are presented. The image detection algorithms are implemented on three representative message-passing architectures: a low-cost heterogeneous PVM network, an Intel iPSC/860 hypercube, and a CM-5 massively parallel multicomputer. Our objectives are to provide insight into implementation and performance issues for image processing applications on general-purpose message-passing architectures, to investigate implications an network variations, and to evaluate the computing scalabilities on the three network systems by examining execution and communication patterns of the image edge detection application. >
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Model-based OpenMP implementation of a 3D facial pose tracking system
Sankalita Saha,Chung-Ching Shen,Chia-Jui Hsu,Gaurav Aggarwal,Ashok Veeraraghavan,Alan Sussman,Shuvra S. Bhattacharyya +6 more
- 14 Aug 2006
TL;DR: This paper describes the implementation of a 3D facial pose tracking system using the OpenMP platform, based on a design methodology that uses coarse-grain dataflow graphs to model and schedule the application.
14
Refining edge detection within spiral architecture
Xiangjian He,Tom Hintz +1 more
- 31 Jan 2000
TL;DR: An edge detection scheme using Gaussian Multi-resolution Theory is presented that reduces noise and unnecessary details of the image and is applied to obtain the edge maps of some well-known images for image processing.
12
An Efficient Parallel Algorithm for Computing the Gaussian Convolution of Multi-dimensional Image Data
TL;DR: A parallel convolution algorithm for estimating the partial derivatives of 2D and 3D images on distributed-memory MIMD architectures by exploiting the separable characteristics of the Gaussian filter.
Replicated shared object model for parallel edge detection algorithm based on spiral architecture
TL;DR: A parallel edge detection algorithm based on spiral architecture is designed in this paper to meet the requirements of replicated object management, update propagation, underlying communication and consistency maintenance among replicated objects.
5
Fast object recognition by parallel image matching on a distributed system
Jia You,W.P. Zhu,H.A. Cohen,E. Pissaloux +3 more
- 25 Oct 1995
TL;DR: The development of a parallel image matching system which uses a divide-and-conquer method to implement the proposed hierarchical matching scheme on a networked workstation cluster shows that a distributed workstation Cluster can best meet the demand of high computation and memory access in image processing.
4
References
A Computational Approach to Edge Detection
TL;DR: There is a natural uncertainty principle between detection and localization performance, which are the two main goals, and with this principle a single operator shape is derived which is optimal at any scale.
29.9K
Edge Focusing
TL;DR: It is shown that ``edge focusing'', i.e., a coarse-to-fine tracking in a continuous manner, combines high positional accuracy with good noise-reduction, which is of vital interest in several applications.
524
Communication and computation performance of the CM-5
T. T. Kwan,B. K. Totty,Daniel A. Reed +2 more
- 01 Dec 1993
TL;DR: To assess the scalability of the CM-5's computation and interprocessor communication rates, a series of benchmarks was used to measure the performance of theCM-5 data and control networks, the node vector units, and the balance of computation and communication.
34
Communication and computation patterns of large scale image convolutions on parallel architectures
S.G. Dykes,Xiaodong Zhang,Yan Zhou,Haixu Yang +3 more
- 01 Apr 1994
TL;DR: An analysis of a texture segmentation application containing a 96/spl times/96 convolution indicates for large kernel convolutions the size and bandwidth of the fast memory store is more important than processor power or communication overhead.
27
How to get good performance from the CM-5 data network
Eric Brewer,Bradley C. Kuszmaul +1 more
- 01 Apr 1994
TL;DR: Architectural support for global barriers, injection reordering, and flow control may be worthwhile for achieving good communications performance.