An improved tracking technique for visual measurements of ionic polymer–metal composites (IPMC) actuators using Compute Unified Device Architecture (CUDA)

The implementation of a real-time measurement system based on visual measurements of displacement of an actuator–cantilever is presented in this paper. This work is aimed at accelerating image processing for the fast tracking of small actuators based on ionic polymer–metal composites using the graphics processing unit (GPU) approach. The proposed processing techniques for point tracking are based on the analysis of subsequent images of the moving item. The area-segmentation approach is used which combines region prediction, successive scanning, edge filtering and match processing. The overall implementation uses the CPU and GPU, while the results achieved indicate that the computation process speeds up by more than 40 × . This is a quite useful improvement especially for real-time measurement and control applications of closed-loop systems based on IPMC materials.