Cover Image

Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor

The uncontrolled population of the submerged aquatic vegetation (SAV) in the shallow lake leads to water quality deterioration, which negatively impacts the beauty of its surroundings and limits the recreational activities of the community there. One of the lakes affected by this problem is Communit...

Full description

Saved in:
Bibliographic Details
Main Authors: Misnan, Mohamad Farid, Azri, Muhamad Alif Izani, M. Thamrin, Norashikin, Nik Ibrahim, Nik Norliyana
Format: Conference or Workshop Item
Published: IEEE 2023
Online Access:http://psasir.upm.edu.my/id/eprint/44152/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.upm.eprints.44152
record_format eprints
spelling my.upm.eprints.441522023-12-25T11:08:12Z http://psasir.upm.edu.my/id/eprint/44152/ Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor Misnan, Mohamad Farid Azri, Muhamad Alif Izani M. Thamrin, Norashikin Nik Ibrahim, Nik Norliyana The uncontrolled population of the submerged aquatic vegetation (SAV) in the shallow lake leads to water quality deterioration, which negatively impacts the beauty of its surroundings and limits the recreational activities of the community there. One of the lakes affected by this problem is Community Lake 7/1F Shah Alam, Selangor, Malaysia. One way to overcome this problem is by identifying the distribution of the submerged aquatic vegetation in the lake before applying any treatment to reduce its number. Avoiding unnecessary chemical or bioorganic treatment waste in the lake ecosystem is important, which can invite another problem. An unmanned aerial vehicle (UAV) is an advantage in surveying while estimating the affected area caused by these parasite plants. Unfortunately, identifying the population of this small vegetation accurately from the image requires extensive image processing techniques. To address this issue, this paper presents a population area estimation method for vegetation in shallow lakes based on the Colour Space Model and Edge Detection in image processing. The edge detection technique initially segments and extracts the lake’s boundary from the image. Then, the Color Space Model, with the RGB and YCrCB models, are utilized to find the best area estimation. These techniques are compared, and the YCrCb colour space model estimates the SAV area 12% more accurately than the RGB colour space model. In conclusion, integrating image processing with the UAV in estimating the small vegetation area in a shallow lake is feasible with the high-performance processor and technique. IEEE 2023 Conference or Workshop Item PeerReviewed Misnan, Mohamad Farid and Azri, Muhamad Alif Izani and M. Thamrin, Norashikin and Nik Ibrahim, Nik Norliyana (2023) Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor. In: 2023 IEEE International Conference on Agrosystem Engineering, Technology & Applications (AGRETA), 9 Sept. 2023, Kuala Lumpur, Malaysia. (pp. 1-6). 10.1109/AGRETA57740.2023.10262671
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description The uncontrolled population of the submerged aquatic vegetation (SAV) in the shallow lake leads to water quality deterioration, which negatively impacts the beauty of its surroundings and limits the recreational activities of the community there. One of the lakes affected by this problem is Community Lake 7/1F Shah Alam, Selangor, Malaysia. One way to overcome this problem is by identifying the distribution of the submerged aquatic vegetation in the lake before applying any treatment to reduce its number. Avoiding unnecessary chemical or bioorganic treatment waste in the lake ecosystem is important, which can invite another problem. An unmanned aerial vehicle (UAV) is an advantage in surveying while estimating the affected area caused by these parasite plants. Unfortunately, identifying the population of this small vegetation accurately from the image requires extensive image processing techniques. To address this issue, this paper presents a population area estimation method for vegetation in shallow lakes based on the Colour Space Model and Edge Detection in image processing. The edge detection technique initially segments and extracts the lake’s boundary from the image. Then, the Color Space Model, with the RGB and YCrCB models, are utilized to find the best area estimation. These techniques are compared, and the YCrCb colour space model estimates the SAV area 12% more accurately than the RGB colour space model. In conclusion, integrating image processing with the UAV in estimating the small vegetation area in a shallow lake is feasible with the high-performance processor and technique.
format Conference or Workshop Item
author Misnan, Mohamad Farid
Azri, Muhamad Alif Izani
M. Thamrin, Norashikin
Nik Ibrahim, Nik Norliyana
spellingShingle Misnan, Mohamad Farid
Azri, Muhamad Alif Izani
M. Thamrin, Norashikin
Nik Ibrahim, Nik Norliyana
Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
author_facet Misnan, Mohamad Farid
Azri, Muhamad Alif Izani
M. Thamrin, Norashikin
Nik Ibrahim, Nik Norliyana
author_sort Misnan, Mohamad Farid
title Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
title_short Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
title_full Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
title_fullStr Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
title_full_unstemmed Performance evaluation of RGB and YCrCb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1F Shah Alam, Selangor
title_sort performance evaluation of rgb and ycrcb colour space models for submerge aquatic vegetation area estimation in the shallow lake 7/1f shah alam, selangor
publisher IEEE
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/44152/
_version_ 1787137177669337088
score 13.211869

Similar Items