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Characterization of a Stereo Vision System for Object Classification for USV Navigation.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Characterization of a Stereo Vision System for Object Classification for USV Navigation./
Author:	Kaplowitz, Chad.
Description:	1 online resource (119 pages)
Notes:	Source: Masters Abstracts International, Volume: 84-03.
Contained By:	Masters Abstracts International84-03.
Subject:	Ocean engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29328262click for full text (PQDT)
ISBN:	9798841786184

Characterization of a Stereo Vision System for Object Classification for USV Navigation.
Kaplowitz, Chad.

Characterization of a Stereo Vision System for Object Classification for USV Navigation. - 1 online resource (119 pages)

Source: Masters Abstracts International, Volume: 84-03.

Thesis (M.S.)--Florida Atlantic University, 2022.

Includes bibliographical references

This experiment used different methodologies and comparisons that helped to determine the direction of future research on water-based perception systems for unmanned surface vehicles (USV) platforms. This would be using a stereo-vison based system. Presented in this work is object color and shape classification in the real-time maritime environment. This was coupled with HSV color space that allowed for different thresholds to be identified and detected. The algorithm was then calibrated and executed to configure the depth, color and shape accuracies. The approach entails the characterization of a stereo-vision camera and mount that was designed with 8.5° horizontal viewing increments and mounted on the WAMV.This characterization has depth, color and shape object detection and its classification. Different shapes and buoys were used to complete the testing with assorted colors and shapes. The main program used was OpenCV which entails Gaussian blurring, Morphological operators and Canny edge detection libraries with a ROS integration. The code focuses on the area size and the number of contours detected on the shape for successes. A summary of what this thesis entails is the installation and characterization of the stereovision system on the WAMV-USV by obtaining specific inputs to the high-level controller.Majority of the testing that the WAMV was used for had a perception depth of 12.5ft and 19ft away. Green had acceptable results, especially with triangles at 12.5ft away with an 89.1% classification accuracy. While Orange had the best rectangle results which is still relatively low at 18.6% classification accuracy. These numbers are consistent due to the rectangle fabric not staying in place correctly due to wind and larger area, the triangle fabric did. Additionally, the depth percent error was low unless the reflection caused it to constantly read a shorter depth.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798841786184Subjects--Topical Terms:

660731
Ocean engineering.
Subjects--Index Terms:

PerceptionIndex Terms--Genre/Form:

542853
Electronic books.

Characterization of a Stereo Vision System for Object Classification for USV Navigation.
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100 1 $a Kaplowitz, Chad. $3 3695297
245 1 0 $a Characterization of a Stereo Vision System for Object Classification for USV Navigation.
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500 $a Source: Masters Abstracts International, Volume: 84-03.
500 $a Advisor: Dhanak, Manhar.
502 $a Thesis (M.S.)--Florida Atlantic University, 2022.
504 $a Includes bibliographical references
520 $a This experiment used different methodologies and comparisons that helped to determine the direction of future research on water-based perception systems for unmanned surface vehicles (USV) platforms. This would be using a stereo-vison based system. Presented in this work is object color and shape classification in the real-time maritime environment. This was coupled with HSV color space that allowed for different thresholds to be identified and detected. The algorithm was then calibrated and executed to configure the depth, color and shape accuracies. The approach entails the characterization of a stereo-vision camera and mount that was designed with 8.5° horizontal viewing increments and mounted on the WAMV.This characterization has depth, color and shape object detection and its classification. Different shapes and buoys were used to complete the testing with assorted colors and shapes. The main program used was OpenCV which entails Gaussian blurring, Morphological operators and Canny edge detection libraries with a ROS integration. The code focuses on the area size and the number of contours detected on the shape for successes. A summary of what this thesis entails is the installation and characterization of the stereovision system on the WAMV-USV by obtaining specific inputs to the high-level controller.Majority of the testing that the WAMV was used for had a perception depth of 12.5ft and 19ft away. Green had acceptable results, especially with triangles at 12.5ft away with an 89.1% classification accuracy. While Orange had the best rectangle results which is still relatively low at 18.6% classification accuracy. These numbers are consistent due to the rectangle fabric not staying in place correctly due to wind and larger area, the triangle fabric did. Additionally, the depth percent error was low unless the reflection caused it to constantly read a shorter depth.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Ocean engineering. $3 660731
650 4 $a Computer science. $3 523869
653 $a Perception
653 $a Stereo-vision
653 $a WAMV
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0547
690 $a 0984
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Florida Atlantic University. $b Ocean Engineering. $3 3173823
773 0 $t Masters Abstracts International $g 84-03.
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