Summary: This article presents an architecture based on FPGA for the calculation of texture attributes using an adequacy of the technique of sum and differences of histograms. The attributes calculated by this architecture will be used in a process of classification for identification of objects during the navigation of an autonomous robot of service. Because of that, the constraint of real-time execution plays an essential role during the architecture design. So, the architecture is designed to calculate 30 dense images with 6 different attributes of texture for 10 different displacements. Exploiting the reuse of operations in parallel on the FPGA and taking into account the requisites in the time of calculation, it is possible to use the resources in an efficient and optimised way in order to obtain an architecture with the best trade off between resources and the time of calculation. Thanks to the high performance of this architecture, it can be used in applications like medical diagnosis or target detection.