Partial Order Rank Features in Colour Space

Fabrizio Smeraldi, Francesco Bianconi, Antonio Fernández, Elena González
2020 Applied Sciences  
Partial orders are the natural mathematical structure for comparing multivariate data that, like colours, lack a natural order. We introduce a novel, general approach to defining rank features in colour spaces based on partial orders, and show that it is possible to generalise existing rank based descriptors by replacing the order relation over intensity values by suitable partial orders in colour space. In particular, we extend a classical descriptor (the Texture Spectrum) to work with partial
more » ... o work with partial orders. The effectiveness of the generalised descriptor is demonstrated through a set of image classification experiments on 10 datasets of colour texture images. The results show that the partial-order version in colour space outperforms the grey-scale classic descriptor while maintaining the same number of features.
doi:10.3390/app10020499 fatcat:f4veho3f3jetjhhzyce6wreo4a