Show simple item record

dc.contributor.advisorUddin, Jia
dc.contributor.authorHossain, Md. Kamal
dc.contributor.authorIbtehaz, Md. Asif
dc.contributor.authorAshique, Md. Assaduzzaman
dc.date.accessioned2016-05-22T16:11:07Z
dc.date.available2016-05-22T16:11:07Z
dc.date.copyright2016
dc.date.issued2016-04
dc.identifier.otherID 12101073
dc.identifier.otherID 14341001
dc.identifier.otherID 12301017
dc.identifier.urihttp://hdl.handle.net/10361/5313
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 30-33).
dc.description.abstractEdge detection is a considerably important factor in image or video processing. Detecting the edges of an image play a significant role in image segmentation, data compression, well matching, and image reconstruction. There are several approaches available to detect the edges of an image. In this paper we focus on Sobel edge detection using contract-time anytime algorithm in CUDA. To reduce the computational complexity we implemented our proposed edge detection method using an NVIDIA GPU. In the experimental setup we have used NVIDIA GTX 550Ti GPU along with AMD FX8150 Processor and 8 GB RAM. Finally, we measure speedup as well as quick, moderate and final (3steps of contract) of our proposed parallel implemented model. Comparing with conventional serial CPU based edge detection we have experienced maximum 4X speedup of proposed implementation for 16 block dimension.en_US
dc.description.statementofresponsibilityMd. Kamal Hossain
dc.description.statementofresponsibilityMd. Asif Ibtehaz
dc.description.statementofresponsibilityMd. Assaduzzaman Ashique
dc.format.extent33 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectCSEen_US
dc.subjectComputer science and engineeringen_US
dc.subjectComputational complexityen_US
dc.titleImprove computational complexity of sobel edge detection using parallel contract anytime algorithmen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record