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Quantifying Nonhomogeneous Colors in Agricultural Materials. Part II: Comparison of Machine Vision and Sensory Panel Evaluations
Author(s) -
Balaban M.O.,
Aparicio J.,
Zotarelli M.,
Sims C.
Publication year - 2008
Publication title -
journal of food science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 150
eISSN - 1750-3841
pISSN - 0022-1147
DOI - 10.1111/j.1750-3841.2008.00967.x
Subject(s) - artificial intelligence , color difference , color vision , perception , mathematics , computer vision , sample (material) , sensory system , machine vision , significant difference , pattern recognition (psychology) , statistics , computer science , psychology , cognitive psychology , chemistry , enhanced data rates for gsm evolution , chromatography , neuroscience
The average colors of mangos and apples were measured using machine vision. A method to quantify the perception of nonhomogeneous colors by sensory panelists was developed. Three colors out of several reference colors and their perceived percentage of the total sample area were selected by untrained panelists. Differences between the average colors perceived by panelists and those from the machine vision were reported as Δ E values (color difference error). Effects of nonhomogeneity of color, and using real samples or their images in the sensory panels on Δ E were evaluated. In general, samples with more nonuniform colors had higher Δ E values, suggesting that panelists had more difficulty in evaluating more nonhomogeneous colors. There was no significant difference in Δ E values between the real fruits and their screen image, therefore images can be used to evaluate color instead of the real samples.