Within different techniques for texture modelling and recog-nition, local binary patterns and its variants have received much interest in recent years thanks to their low computational cost and high discrim-ination power. We propose a new texture description approach, whose principle is to extend the LBP representation from the local gray level to the regional distribution level. The region is represented by pre-defined structuring element, while the distribution is approximated using the two first statistical moments. Experimental results on four large texture databases, including Outex, KTH-TIPS 2b, CUReT and UIUC show that our approach significantly improves the performance of texture represen-tation and classification with respect to comparable methods.