Paper Title:
Research on Machine Vision in Forestry Pluck System
  Abstract

Forestry industry is an important part of nation's economy. In this paper, a machine vision system is presented as a key module of Camellia oleifera pluck robot. In order to cut fruit image up from complicate background, SOFM neural network and gray thresh is used in image segmentation. In SOFM method, take R-B,G-R,G-B and hue H tunnel as input feature vectors, use self-organization network to clustering can get the best effect. in gray threshold method can take various of method to get the best threshold, such as PSO and GA algorithm, and MATLAB includes the toolboxes. At last use noise ratio, area ratio, divided time, Fourier boundary descriptors and other indicators to assess the accuracy of segmentation. The methods have the significance to the current and subsequent research of forestry pluck device.

  Info
Periodical
Advanced Materials Research (Volumes 139-141)
Edited by
Liangchi Zhang, Chunliang Zhang and Tielin Shi
Pages
2199-2202
DOI
10.4028/www.scientific.net/AMR.139-141.2199
Citation
X. Li, C. L. Zhang, L. J. Li, Z. Hu, "Research on Machine Vision in Forestry Pluck System", Advanced Materials Research, Vols. 139-141, pp. 2199-2202, 2010
Online since
October 2010
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Price
$32.00
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