Accelerated intuitionistic fuzzy edge detection algorithm by using CUDA

Intuitionistic fuzzy edge detection (IFED) algorithm has been used in the signification or characterization of images. IFED algorithm has been designed by the experts and the algorithm provides to aim to minimize errors of them. To be applicable in parallel of IFED is pave the way for accelerating of algorithm by performing in the graphics card. In this study, IFED algorithm was tested by transferring different size images to graphics cards which has different computing capacity via Compute Unified Device Architecture (CUDA) programming environment which is manufactured by NVIDIA. Parallel model of the algorithm adapted to CUDA platform, compared to serial application running on processor, and has seen that shortened runtime at least 67 times, most 641 times.