Naslov
K-Means Image Segmentation on Massively Parallel GPU Architecture

Autori
Sirotković, Jadran ; Dujmić, Hrvoje ; Papić, Vladan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proc. MIPRO 2012 / - , 2012, 505-511

Skup
MIPRO 2012 - jubilarni 35. međunarodni skup

Mjesto i datum
Opatija, Hrvatska, 21.05.2012. - 25.05.2012

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
image segmentation; GPU programming; CUDA

Sažetak
Image segmentation can be computationally demanding, and therefore require powerful hardware in order to meet performance requirements. Recent rapid increase in the performance of graphic processing unit(GPU) hardware, coupled with simplified programming methods, have made GPU an efficient coprocessor for executing variety of highly parallel applications. This paper presents an implementation of k-means image segmentation on the GPU platform with Compute Unified Device Architecture (CUDA). Parallel k-means segmentation is realized in hybrid manner i.e. proposed approach distributes computation load between Central Processing Unit (CPU) and GPU. The emphasis is placed on adaptation of the core algorithm to efficiently process datasets characteristic for image segmentation while exploiting benefits of underlying GPU hardware architecture. Numerical experiments have demonstrated considerably faster segmentation execution with proposed approach comparing to classical CPU-based approach.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo

POVEZANOST RADA