This paper presents an implementation of the conformal voting scheme using a reconfigurable hardware approach in the frame of conformal geometric algebra G_3,1. This algorithm is able to extract geometric entities, such as circles and lines from edged images. The conformal voting scheme is divided into two main stages: a local stage computed using neighborhoods in the image, and a global stage using the results of the local voting stage. In this implementation, we focused on the most computationally demanding stage: the local stage, which is computed in the field-programmable gate array, while the global voting stage continues to be executed on the PC. The results show an average speedup of 3× depending on the features of the input image and a coefficient of variation near to zero in the times of repeated experiments. Finally, our method can be used for multiple applications in real-time image processing.