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Design considerations in the real-time implementation of multiple expert image classifiers within a modular and flexible multiple-platform design environment

Rahman, Ahmad Fuad Rezaur, Fairhurst, Michael, Lee, Peter (1998) Design considerations in the real-time implementation of multiple expert image classifiers within a modular and flexible multiple-platform design environment. Real-Time Imaging, 4 (5). pp. 361-376. ISSN 1077-2014. (doi:10.1016/S1077-2014(98)90005-5) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:17003)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
http://dx.doi.org/10.1016/S1077-2014(98)90005-5

Abstract

A modular multiple platform design environment is proposed for the real-time implementation of image analysis systems suited to tasks such as visual inspection and other similar applications involving the analysis of two-dimensional (2D) shapes. The design strategies proposed are particularly suited to the implementation of high performance image classifiers based on the multiple expert paradigm. The unified configuration includes an integrated environment incorporating different software and hardware platforms to maximize the overall efficiency of the complete image processing or recognition task. One of the major application areas of such systems is the recognition of handwritten characters. In recent years, a new generation of handwritten recognition systems has been explored which is based on a multiple expert paradigm. The decision combination required for:Ph,,, configurations is a specialized data fusion process. It has been found that these multiple expert decision combination configurations dan easily outperform most of the individual experts working on their own, but successful integration of decisions taken by multiple experts depends not only on the access to different individual algorithms implemented and applied independently, but also on optimized implementations of these individual algorithms. It has been demonstrated that different image processing and recognition algorithms cannot be completely optimized on a single implementation platform. On the contrary, it has been found that different processes can be implemented with maximum efficiency on different platforms. In this paper, comparative performance analysis of the same algorithms on different platforms has been carried out to select the optimum implementation platform for different algorithms in terms of complexity and execution time constraints with the aim of implementing various multiple expert decision combination configurations, and very encouraging results have been achieved. This reasoning has been further explored to build a generalized, flexible and modular design environment to facilitate the incorporation of pipelined multiple platform implementations suitable for a range of image processing, image analysis and computer vision applications.

Item Type: Article
DOI/Identification number: 10.1016/S1077-2014(98)90005-5
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > Q Science (General) > Q335 Artificial intelligence
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Tara Puri
Date Deposited: 07 Jul 2009 11:39 UTC
Last Modified: 16 Nov 2021 09:55 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/17003 (The current URI for this page, for reference purposes)

University of Kent Author Information

Fairhurst, Michael.

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CReDIT Contributor Roles:

Lee, Peter.

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