Texture classification using rotation invariant LBP based on digital polygons

Abstract

This paper investigates the use of digital polygons as a replacement for circular interpolated neighbourhoods for extracting texture features through Local Binary Patterns. The use of digital polygons has two main advantages: reduces the computational cost, and avoids the high-frequency loss resulting from pixel interpolation. The solution proposed in this work employs a sub-sampling scheme over Andres’ digital circles. The effectiveness of the method was evaluated in a supervised texture classification experiment over eight different datasets. The results showed that digital polygons outperformed interpolated circular neighbourhoods in most cases.