Paper Title:
Preliminary Study on Quantification of Duck Color Based on Fuzzy K – Nearest Neighbor Method
  Abstract

In order to quantify duck color quickly and accurately, a visible light image acquisition system was developed in this study. Firstly, duck breast meat was extraced from the original image using over-threshold segmentation method; and then image fleshcolor features including average value of L*,a* and b* were extracted through color space conversion; finally, fleshcolor features were used as characteristic parameters to establish quantification model for duck color based on the method of Fuzzy k-nearest neighbor (F KNN) and BP neural network and the experimental datas gotten from the two methods were analyzd in contrast. The results showed the accuracy rate of test samples by F KNN method was higher than that of BP neural network, the accuracy rate was 83.78% and 78.38% respectively. Therefore, F KNN method was selected for quantification of duck color in this research.

  Info
Periodical
Edited by
Yuanzhi Wang
Pages
210-215
DOI
10.4028/www.scientific.net/AMM.39.210
Citation
D. C. Tu, J. H. Zhao, M. H. Liu, J. Shen, F. Yu, "Preliminary Study on Quantification of Duck Color Based on Fuzzy K – Nearest Neighbor Method", Applied Mechanics and Materials, Vol. 39, pp. 210-215, 2011
Online since
November 2010
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