ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
advertisementadvertisement
Pattern Recognition Letters
Volume 18, Issue 1, January 1997, Pages 63-72
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Purchase PDF (517 K)

  E-mail Article   
  Add to my Quick Links   
Bookmark and share in 2collab (opens in new window)
Request permission to reuse this article
  Cited By in Scopus (0)
 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/S0167-8655(96)00128-6    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1997 Elsevier B.V. All rights reserved.

Vectorizations of randomized matching for run-length coded strings

Kuo-Liang ChungCorresponding Author Contact Information, a, Corresponding Author Contact Information, E-mail The Corresponding Author and Wen-Ming Yanb

a Department of Information Management, National Taiwan Institute of Technology, No. 43, Section 4, Keelung Road, Taipei, Taiwan 10672, ROC b Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan 10764, ROC

Received 11 April 1996; 
Revised 21 November 1996. 
Available online 12 May 1998.

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Abstract

Matching run-length coded strings (RLCSs) is very important in the field of pattern recognition. This paper considers the design of vectorized matching algorithms that operate directly on RLCSs. We first modify the algorithm of Karp and Rabin (1987) to design a linear-time randomized matching algorithm for RLCSs. Following this algorithm, two new and fast vectorized algorithms are presented. The first one is off-line and the second one is on-line. Some experiments are carried out on a CRAY X-MP EA/ 116se vector supercomputer to demonstrate the good performance of our vectorized algorithms.

Author Keywords: Pattern matching; Randomized algorithms; Vectorized algorithms; Run-length coded strings; Error probability; Vector supercomputer

Article Outline

• Further Reading

 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.