A Multi-Agent System for Parallelizing Image Analysis Tasks

To exploit the full capacity of distributed systems for image analysis tasks they must be processed in parallel. However, developing parallel programs is complicated and often results in architecture-dependent code that is diicult to port to diierent machines. Thus there is the need of more exi-ble, architecture independent methods for an automatic parallelization of tasks. This paper introduces such a method and describes a multi-agent system for the automatic parallelization of image analysis tasks. The user provides a spec-iication of the task that is used by the agents to plan and control its parallel processing within a distributed system. At this, they make use of diierent methods of parallel processing and consider the speciic qualiication and the actual load of processors when deciding about the scheduling and mapping of tasks and data.

[1]  Chew Lim Tan,et al.  Transputer implementation of a multiple agent model for object tracking , 1995, Pattern Recognit. Lett..

[2]  Anil K. Jain,et al.  Fusion of range and intensity images on a connection machine (CM-2) , 1995, Pattern Recognit..

[3]  Peter Raulefs,et al.  Cooperating Agent Architectures to Manage Manufacturing Processes , 1991, Wissensbasierte Systeme.

[4]  Afonso Ferreira,et al.  Ultra-fast parallel contour tracking, with applications to thinning , 1994, Pattern Recognit..

[5]  Wolfgang Eckstein,et al.  Interactive data inspection and program development for computer vision , 1996, Electronic Imaging.

[6]  Dmitry B. Goldgof,et al.  Parallel algorithms for circle detection in images , 1994, Pattern Recognit..

[7]  Tao Yang,et al.  Heuristic Algorithms for Scheduling Iterative Task Computations on Distributed Memory Machines , 1997, IEEE Trans. Parallel Distributed Syst..

[8]  Rin-ichiro Taniguchi,et al.  Software platform for parallel image processing and computer vision , 1997, Optics & Photonics.

[9]  Gerald Schreiber,et al.  PIPS--A general purpose Parallel Image Processing System , 1994 .

[10]  Osamu Katai,et al.  A Study of Organizational Learning in Multi-Agent Systems , 1996, ECAI Workshop LDAIS / ICMAS Workshop LIOME.

[11]  Tao Yang,et al.  DSC: Scheduling Parallel Tasks on an Unbounded Number of Processors , 1994, IEEE Trans. Parallel Distributed Syst..

[12]  Tao Yang,et al.  A Comparison of Clustering Heuristics for Scheduling Directed Acycle Graphs on Multiprocessors , 1992, J. Parallel Distributed Comput..

[13]  Klaus Jansen,et al.  Off-Line and On-Line Call-Scheduling in Stars and Trees , 1997, WG.