In this paper we investigate the problem of choosing the adequate colour representation for automated surface grading. Specifically, we discuss the pros and cons of different colour spaces, point out some common misconceptions about their use, and propose a number of ‘best practices’ for colour conversion. To put the discussion into practice we generated a new dataset of 25 classes of natural stone products which we used to systematically compare and evaluate the performance of seven device-dependent and three device-independent colour spaces through two classification strategies. With the nearest neighbour classifiers no significant difference emerged among the colour spaces considered, whereas with the linear classifier it was found that device-independent Lab and Luv spaces performed significantly better than the others.
On comparing colour spaces from a performance perspective: application to automated classification of polished natural stones
BIANCONI, Francesco;
2015
Abstract
In this paper we investigate the problem of choosing the adequate colour representation for automated surface grading. Specifically, we discuss the pros and cons of different colour spaces, point out some common misconceptions about their use, and propose a number of ‘best practices’ for colour conversion. To put the discussion into practice we generated a new dataset of 25 classes of natural stone products which we used to systematically compare and evaluate the performance of seven device-dependent and three device-independent colour spaces through two classification strategies. With the nearest neighbour classifiers no significant difference emerged among the colour spaces considered, whereas with the linear classifier it was found that device-independent Lab and Luv spaces performed significantly better than the others.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
