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Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning
Joint Authors
Ha, Ok-Kyoon
Lee, Keonpyo
Kim, Wan-Jin
Yoon, Kun Su
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-03
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Techniques for analyzing and avoiding hazardous objects and situations on the seabed are being developed to ensure the safety of ships and submersibles from various hazards.
Improvements in accuracy and real-time response are critical for underwater object recognition, which rely on underwater sonar detection to remove noises and analyze the data.
Therefore, parallel processing is being introduced for real-time processing of two-dimensional (2D) underwater sonar detector images for seabed monitoring.
However, this requires optimized parallel processing between the modules for image processing and the data processing of a vast amount of data.
This study proposes an effective parallel processing method, called Task Partitioning, based on central and graphical processing units for monitoring and identifying underwater objects in real time based on 2D-imaging sonar.
The practicality of the proposed method is evaluated experimentally by comparing it to the sequential processing method.
The experimental results show that the Task Partitioning method significantly improves the processing time for sonar images because it reduces the average execution time to 1% and 5% of the sequential processing method and general parallelization, respectively.
American Psychological Association (APA)
Ha, Ok-Kyoon& Lee, Keonpyo& Kim, Wan-Jin& Yoon, Kun Su. 2019. Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning. Scientific Programming،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1210767
Modern Language Association (MLA)
Ha, Ok-Kyoon…[et al.]. Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning. Scientific Programming No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1210767
American Medical Association (AMA)
Ha, Ok-Kyoon& Lee, Keonpyo& Kim, Wan-Jin& Yoon, Kun Su. Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning. Scientific Programming. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1210767
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210767