Title
Prediction of panellists' perception of bread crumb appearance using fractal and visual textural features
Date Issued
01 February 2008
Access level
metadata only access
Resource Type
journal article
Author(s)
Butler F.
University College Dublin
Abstract
Ratings of visual characteristics of bread crumb images obtained by panellists were correlated with features obtained by digital fractal and texture analysis and simple thresholding. Trained panellists were asked to rate 168 bread crumb images on fineness, homogeneity and degree of orientation, using continuous line scales. The relative orientation of the main and secondary peaks of the image power spectrum was the only parameter related to the human perception of the degree of crumb orientation. Single fractal dimension terms correlated better with the panellists' perception of grain fineness and homogeneity than the single crumb features from thresholding. Second-order polynomial models were significantly better (P < 0.01) in most predictors than simple linear models. Grain fineness was better approached by the method of relative differential box-counting fractal dimension (R 2 = 0.822) whereas grain homogeneity was highly related to the mass fractal dimension (R 2 = 0.820). Multiple linear models to estimate grain fineness with higher predictive capacity included predictors such as fractal dimension, mean intercellular distance and void fraction (R 2 > 0.860). © 2007 Springer-Verlag.
Start page
779
End page
785
Volume
226
Issue
4
Language
English
OCDE Knowledge area
Alimentos y bebidas
Subjects
Scopus EID
2-s2.0-38349135883
Source
European Food Research and Technology
ISSN of the container
14382377
Source funding
H2020 Food
Sponsor(s)
Acknowledgments The Authors wish to acknowledge that this work was funded by the Irish Department of Agriculture through the Food Institutional Research Measure.
Sources of information:
Directorio de Producción CientÃfica
Scopus