ACCELERATION OF THE EDGE STRENGTH FUNCTION

Authors : Hacer YALIM KELEŞ

Pages : 50-69

Doi:10.1501/commua1-2_0000000096

View : 13 | Download : 5

Publication Date : 2016-10-01

Article Type : Research Paper

Abstract :Edge strength function insert ignore into journalissuearticles values(ESF); generates a family of level curves that evolves under the influence of curvature motions. This function is proved to be useful in representing images in computer vision for analysis and recognition purposes in different contexts. Computation of the ESF requires solving a partial differential equation, hence computationally costly. In this work, we present two parallel implementations of ESF that work on Graphics Processing Units insert ignore into journalissuearticles values(GPU); using Compute Unified Design Architecture insert ignore into journalissuearticles values(CUDA);. Both implementations reduce the computational time significantly with respect to their serial counterpart. The implementations differ mainly in the type of memory that is utilized for accessing data; the first approach utilizes the shared memory and the second one utilizes the texture memory. We obtain between 40 to 65 times speedup in the shared memory based implementation and between 35 to 55 times in the texture memory based implementation with respect to the single threaded CPU implementation. The amount of speedup changes depending on the data size
Keywords : Edge strength function, parallelization, general purpose programming on graphics processing units, compute unified device architecture