A statistics-guided progressive RAST algorithm for peak template matching in GCxGC

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Comprehensive two-dimensional gas chromatography (GCxGC) is an emerging technology for chemical separation. Chemical identification is one of the critical tasks in GCxGC analysis. Peak template matching is a technique for automatic chemical identification. Peak template matching can be formulated as a point pattern matching problem. This paper proposes a progressive RAST algorithm to solve the problem. Search space pruning techniques based on peak location distributions and transformation distributions are also investigated for guided search. Experiments on seven real data sets indicate that the new techniques are effective.

Original languageEnglish (US)
Title of host publicationIEEE Workshop on Statistical Signal Processing Proceedings
PublisherIEEE Computer Society
Pages383-386
Number of pages4
Volume2003-January
ISBN (Print)0780379977
DOIs
StatePublished - 2003
EventIEEE Workshop on Statistical Signal Processing, SSP 2003 - St. Louis, United States
Duration: Sep 28 2003Oct 1 2003

Other

OtherIEEE Workshop on Statistical Signal Processing, SSP 2003
CountryUnited States
CitySt. Louis
Period9/28/0310/1/03

Fingerprint

Template matching
Template Matching
Statistics
Pattern matching
Gas chromatography
Gas Chromatography
Pattern Matching
Matching Problem
Pruning
Search Space
Experiments
Experiment

Keywords

  • Chemical analysis
  • Chemical engineering
  • Chemical processes
  • Chemical technology
  • Computer science
  • Data visualization
  • Gas chromatography
  • Image analysis
  • Pattern matching
  • Space technology

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Signal Processing
  • Computer Science Applications

Cite this

Ni, M., & Reichenbach, S. E. (2003). A statistics-guided progressive RAST algorithm for peak template matching in GCxGC. In IEEE Workshop on Statistical Signal Processing Proceedings (Vol. 2003-January, pp. 383-386). [1289425] IEEE Computer Society. https://doi.org/10.1109/SSP.2003.1289425

A statistics-guided progressive RAST algorithm for peak template matching in GCxGC. / Ni, Mingtian; Reichenbach, Stephen E.

IEEE Workshop on Statistical Signal Processing Proceedings. Vol. 2003-January IEEE Computer Society, 2003. p. 383-386 1289425.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ni, M & Reichenbach, SE 2003, A statistics-guided progressive RAST algorithm for peak template matching in GCxGC. in IEEE Workshop on Statistical Signal Processing Proceedings. vol. 2003-January, 1289425, IEEE Computer Society, pp. 383-386, IEEE Workshop on Statistical Signal Processing, SSP 2003, St. Louis, United States, 9/28/03. https://doi.org/10.1109/SSP.2003.1289425
Ni M, Reichenbach SE. A statistics-guided progressive RAST algorithm for peak template matching in GCxGC. In IEEE Workshop on Statistical Signal Processing Proceedings. Vol. 2003-January. IEEE Computer Society. 2003. p. 383-386. 1289425 https://doi.org/10.1109/SSP.2003.1289425
Ni, Mingtian ; Reichenbach, Stephen E. / A statistics-guided progressive RAST algorithm for peak template matching in GCxGC. IEEE Workshop on Statistical Signal Processing Proceedings. Vol. 2003-January IEEE Computer Society, 2003. pp. 383-386
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