Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory

Mahendra, V. S.S. Prasad, S. Dutta Gupta

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

A machine vision system is described to sort the regenerated plants of gladiolus into groups using trichromatic features of leaves. The machine vision system consisted of a scanner, image analysis software and an adaptive resonance theory neural network. Leaf attributes extracted from the image histograms and used for network classification are the mean brightness, grey-scale level and the maximum pixel count. The system was able to sort the regenerated plants into two distinct groups based on the photometric behaviour. Vigilance parameter had a significant effect on grouping. The approach may provide a means of selecting plants suitable for ex vitro transfer and also helps in quality control of commercial micropropagation.

Original languageEnglish
Pages (from-to)348-353
Number of pages6
JournalCurrent Science
Volume87
Issue number3
Publication statusPublished - 10-08-2004
Externally publishedYes

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Gladiolus
sorting
computer vision
scanners
micropropagation
neural networks
quality control
leaves
image analysis
taxonomy

All Science Journal Classification (ASJC) codes

  • General

Cite this

Mahendra, Prasad, V. S. S., & Dutta Gupta, S. (2004). Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory. Current Science, 87(3), 348-353.
Mahendra ; Prasad, V. S.S. ; Dutta Gupta, S. / Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory. In: Current Science. 2004 ; Vol. 87, No. 3. pp. 348-353.
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Mahendra, Prasad, VSS & Dutta Gupta, S 2004, 'Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory', Current Science, vol. 87, no. 3, pp. 348-353.

Trichromatic sorting of in vitro regenerated plants of gladiolus using adaptive resonance theory. / Mahendra; Prasad, V. S.S.; Dutta Gupta, S.

In: Current Science, Vol. 87, No. 3, 10.08.2004, p. 348-353.

Research output: Contribution to journalArticle

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