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Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform
by
Tian, Yun
, Wang, Min
, Chen, Lichao
, Cao, Jianfang
in
Algorithms
/ Architectural engineering
/ Big Data
/ Cloud computing
/ Computer peripherals
/ Data management
/ Data processing
/ Datasets
/ Design
/ Design optimization
/ Edge detection
/ Edge detection (Image processing)
/ Image detection
/ Image retrieval
/ Mathematical problems
/ Methods
/ Morphology
/ Parallel processing
/ Parallel programming
/ Parallel programming (Computer science)
/ Pascal (programming language)
/ Remote sensing
/ Run time (computers)
2018
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Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform
by
Tian, Yun
, Wang, Min
, Chen, Lichao
, Cao, Jianfang
in
Algorithms
/ Architectural engineering
/ Big Data
/ Cloud computing
/ Computer peripherals
/ Data management
/ Data processing
/ Datasets
/ Design
/ Design optimization
/ Edge detection
/ Edge detection (Image processing)
/ Image detection
/ Image retrieval
/ Mathematical problems
/ Methods
/ Morphology
/ Parallel processing
/ Parallel programming
/ Parallel programming (Computer science)
/ Pascal (programming language)
/ Remote sensing
/ Run time (computers)
2018
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Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform
by
Tian, Yun
, Wang, Min
, Chen, Lichao
, Cao, Jianfang
in
Algorithms
/ Architectural engineering
/ Big Data
/ Cloud computing
/ Computer peripherals
/ Data management
/ Data processing
/ Datasets
/ Design
/ Design optimization
/ Edge detection
/ Edge detection (Image processing)
/ Image detection
/ Image retrieval
/ Mathematical problems
/ Methods
/ Morphology
/ Parallel processing
/ Parallel programming
/ Parallel programming (Computer science)
/ Pascal (programming language)
/ Remote sensing
/ Run time (computers)
2018
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Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform
Journal Article
Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform
2018
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Overview
The Canny operator is widely used to detect edges in images. However, as the size of the image dataset increases, the edge detection performance of the Canny operator decreases and its runtime becomes excessive. To improve the runtime and edge detection performance of the Canny operator, in this paper, we propose a parallel design and implementation for an Otsu-optimized Canny operator using a MapReduce parallel programming model that runs on the Hadoop platform. The Otsu algorithm is used to optimize the Canny operator’s dual threshold and improve the edge detection performance, while the MapReduce parallel programming model facilitates parallel processing for the Canny operator to solve the processing speed and communication cost problems that occur when the Canny edge detection algorithm is applied to big data. For the experiments, we constructed datasets of different scales from the Pascal VOC2012 image database. The proposed parallel Otsu-Canny edge detection algorithm performs better than other traditional edge detection algorithms. The parallel approach reduced the running time by approximately 67.2% on a Hadoop cluster architecture consisting of 5 nodes with a dataset of 60,000 images. Overall, our approach system speeds up the system by approximately 3.4 times when processing large-scale datasets, which demonstrates the obvious superiority of our method. The proposed algorithm in this study demonstrates both better edge detection performance and improved time performance.
Publisher
Hindawi Publishing Corporation,Hindawi,John Wiley & Sons, Inc
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