Open AccessA REVIEW ON IMAGE SEGMENTATION USING GPU
Author(s) -
Gurpreet Kaur,
Sonika Jindal
Publication year - 2016
Publication title -
international journal of computer and technology
Language(s) - English
Resource type - Journals
ISSN - 2277-3061
DOI - 10.24297/ijct.v15i10.4502
Subject(s) - computer science , cuda , segmentation , image segmentation , artificial intelligence , computer vision , graphics processing unit , image processing , image (mathematics) , graphics , representation (politics) , pixel , computer graphics (images) , scale space segmentation , computer graphics , segmentation based object categorization , parallel computing , politics , political science , law
Image Segmentations play a heavy role in areas such as computer vision and image processing due to its broad usage and immense applications. Because of the large importance of image segmentation a number of algorithms have been proposed and different approaches have been adopted. Segmentation divides an image into distinct regions containing each pixel with similar attributes. The objective of apportioning is to simplify and/or alter the representation of an image into something that is more meaningful and more comfortable to break down. This paper discusses the various techniques implemented for image segmentation and discusses the various Computations that can be performed on the graphics processing unit (GPU) by means of the CUDA architecture in order to achieve fast performance and increase the utilization of available system resources.