Image assessment tool for plant health and growth tracking with structural similarity and vegetation index

Software supporting the measurements of leaf area using digital photographs requires a frame reference such as a manual ruler scale to derive the surface areas. Two wellknown image software are ImageJ and EasyLeafArea. Each software uses a thresholdbased approach in pixel count, coupled with calibr...

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Main Author: Koh, Barry Jun Yong
Other Authors: Ng Yin Kwee
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/158596
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1585962022-06-06T02:56:39Z Image assessment tool for plant health and growth tracking with structural similarity and vegetation index Koh, Barry Jun Yong Ng Yin Kwee School of Mechanical and Aerospace Engineering MYKNG@ntu.edu.sg Engineering::Mechanical engineering Software supporting the measurements of leaf area using digital photographs requires a frame reference such as a manual ruler scale to derive the surface areas. Two wellknown image software are ImageJ and EasyLeafArea. Each software uses a thresholdbased approach in pixel count, coupled with calibration to avoid perspective distortion, before deriving the surface areas. However, both are unable to provide an assessment of the leaf’s health. Assessing the health of the leaves is done through the observation of any discolouration. In this study, an assessment tool is created to calculate the plant’s surface area as well as monitor the health of the leaves. Aruco markers are used as reference to calculate leaf surface area. Perspective Distortion errors present in the images are taken into consideration through the usage of a clear and consistent pattern. Images are processed and transformed from Red, Green, Blue (RGB) to Hue, Saturation and Value (HSV) colour space. The health of the leaves is monitored by detecting discolouration using HSV. Finally, the assessment tool can track the growth of the leaves through contour detection and provide information to users on the conditions of the plant’s health. Bachelor of Engineering (Mechanical Engineering) 2022-06-06T02:56:39Z 2022-06-06T02:56:39Z 2022 Final Year Project (FYP) Koh, B. J. Y. (2022). Image assessment tool for plant health and growth tracking with structural similarity and vegetation index. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158596 https://hdl.handle.net/10356/158596 en B165 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Koh, Barry Jun Yong
Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
description Software supporting the measurements of leaf area using digital photographs requires a frame reference such as a manual ruler scale to derive the surface areas. Two wellknown image software are ImageJ and EasyLeafArea. Each software uses a thresholdbased approach in pixel count, coupled with calibration to avoid perspective distortion, before deriving the surface areas. However, both are unable to provide an assessment of the leaf’s health. Assessing the health of the leaves is done through the observation of any discolouration. In this study, an assessment tool is created to calculate the plant’s surface area as well as monitor the health of the leaves. Aruco markers are used as reference to calculate leaf surface area. Perspective Distortion errors present in the images are taken into consideration through the usage of a clear and consistent pattern. Images are processed and transformed from Red, Green, Blue (RGB) to Hue, Saturation and Value (HSV) colour space. The health of the leaves is monitored by detecting discolouration using HSV. Finally, the assessment tool can track the growth of the leaves through contour detection and provide information to users on the conditions of the plant’s health.
author2 Ng Yin Kwee
author_facet Ng Yin Kwee
Koh, Barry Jun Yong
format Final Year Project
author Koh, Barry Jun Yong
author_sort Koh, Barry Jun Yong
title Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
title_short Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
title_full Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
title_fullStr Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
title_full_unstemmed Image assessment tool for plant health and growth tracking with structural similarity and vegetation index
title_sort image assessment tool for plant health and growth tracking with structural similarity and vegetation index
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/158596
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