ArticleComputational intelligence and neuroscience2018
Implementing a Parallel Image Edge Detection Algorithm Based on the Otsu-Canny Operator on the Hadoop Platform.
Article in Computational intelligence and neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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15 citing papers in PubMed.
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- Research on plasma arc flame length detection technology based on region of interest.PloS one · 2025Article
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- Image Enhancement via Special Functions and Its Application for Near Infrared Imaging.Global challenges (Hoboken, NJ) · 2023Article
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- Quantification and Characterization of CTCs and Clusters in Pancreatic Cancer by Means of the Hough Transform Algorithm.International journal of molecular sciences · 2023Article
- A proposed scenario to improve the Ncut algorithm in segmentation.Frontiers in big data · 2023Article
- Magnetic Resonance Imaging Image Segmentation under Edge Detection Intelligent Algorithm in Diagnosis of Surgical Wrist Joint Injuries.Contrast media & molecular imaging · 2021Article
- Internet of Things-Based Ultrasound-Guided Erector Spinae Plane Block Combined with Edaravone Anesthesia in Thoracoscopic Lobectomy.Journal of healthcare engineering · 2021Article
- Bone Cancer Detection Using Feature Extraction Based Machine Learning Model.Computational and mathematical methods in medicine · 2021Article
- Novel Laser-Based Obstacle Detection for Autonomous Robots on Unstructured Terrain.Sensors (Basel, Switzerland) · 2020Article
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- Experimental Study on Nano-Parameters of Styrene-Butadiene-Styrene Block Copolymer Modified Bitumen Based on Atomic Force Microscopy.Polymers · 2019Article
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4 authors.
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Abstract
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.
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