Performance analysis of colour descriptors for parquet sorting

In this paper we consider the problem of colour-based sorting hardwood parquet slabs into lots of similar visual appearance. As a basis for the development of an expert system to perform this task, we experimentally investigate and compare the performance of various colour descriptors (i.e.: soft descriptors, percentiles, marginal histograms and 3D histogram), and colour spaces (i.e.: RGB, HSV and CIE Lab). The results show that simple and compact colour descriptors, such as the mean of each colour channel, are as accurate as more complicated features. Likewise, we found no statistically significant difference in the accuracy attainable through the colour spaces considered in the paper. Our experiments also show that most methods are fast enough for real-time processing. The results suggest the use of simple statistical descriptors along with RGB data as the best practice to approach the problem.

► We present a comparative performance analysis of colour descriptors and spaces for parquet sorting.
► We found no statistically significant difference in the accuracy of the colour descriptors and spaces considered in the experiments.
► Fast and accurate parquet sorting can be obtained through simple statistical descriptors in the RGB colour space.