Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/35994
Title: Processing Large Amounts of Images on Hadoop with OpenCV
Authors: Epanchintsev, T.
Sozykin, A.
Issue Date: 2015
Publisher: Уральский федеральный университет
Citation: Epanchintsev T. Processing Large Amounts of Images on Hadoop with OpenCV / T. Epanchintsev, A. Sozykin // Proceedings of the 1st Ural Workshop on Parallel, Distributed, and Cloud Computing for Young Scientists (Ural-PDC 2015). — Yekaterinburg, 2015. — P. 137-143. — (CEUR Workshop Proceedings ; vol. 1513).
Abstract: Modern image collections cannot be processed efficiently on one computer due to large collection sizes and high computational costs of modern image processing algorithms. Hence, image processing often requires distributed computing. However, distributed computing is a complicated subject that demands deep technical knowledge and often cannot be used by researches who develop image processing algorithms. The framework is needed that allows the researches to concentrate on image processing tasks and hides from them the complicated details of distributed computing. In addition, the framework should provide the researches with the familiar image processing tools. The paper describes the extension to the MapReduce Image Processing (MIPr) framework that provides the ability to use OpenCV in Hadoop cluster for distributed image processing. The modified MIPr framework allows the development of image processing programs in Java using the OpenCV Java binding. The performance testing of created system on the cloud cluster demonstrated near-linear scalability.
Keywords: OPENCV
HADOOP
MAPREDUCE
IMAGE PROCESSING
DISTRIBUTED PROCESSING
URI: http://hdl.handle.net/10995/35994
Conference name: 1st Ural Workshop on Parallel, Distributed, and Cloud Computing for Young Scientists (Ural-PDC 2015)
Conference date: 17.11.2015
ISSN: 1613-0073
Origin: CEUR Workshop Proceedings. Vol. 1513 : Proceedings of the 1st Ural Workshop on Parallel, Distributed, and Cloud Computing for Young Scientists (Ural-PDC 2015). — Yekaterinburg, 2015
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