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

Author(s): Gupta, S.D. | Prasad, V.S.S. |

Year: 2004

Citation: CURRENT SCIENCE Volume: 87 Issue: 3 Pages: 348-353

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.

Topics: Image Analysis, Machine Learning, Applications: Biological Classification, Models: ART 2 / Fuzzy ART,

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