78 research outputs found
A Machine Vision system for real-time and automatic assessment of olives colour and surface defects
Colour mixing modelling and simulation: optimization of colour recipe for carded fibres
Colour matching between carded and finished fibres is an important
challenge for textile industry. The straightforward approach for
mixing together some differently coloured fibres in order to
obtain a blend of a desired colour is to perform a trial and error
approach starting from a given colour recipe and optimizing it
with several attempts. Unfortunately, dyeing process so as the
carding procedure may result in a carded fibre whose colour is
different from the desired one. As a consequence textile companies
have to modify the original recipe in order to reduce the gap
between the colour of the final product and the desired one. The
present work describes a model able to simulate the colour mixing
of fibres in order to assess the best recipe. The model consists
in two modules: a “prediction module” predicts the colour of a
blend obtained by mixing together several fibres; an “optimization
module” is used to optimize the final recipe. The devised system
has been tested for optimizing the recipe of a set of 200 blends.
The mean error in predicting the blend colour is about 15% with a
variance of 0.165. The time for optimizing the recipe is reduced
by 92%
Real-time estimation of peroxides and acidity level of extra-virgin olive oil: an integrated approach
Real-time estimation of olive oil quality parameters: a combined approach based on ANNs and Machine Vision
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