Grass Leaf Identification Using dbN Wavelet and CILBP

Grass is one of the most important resources in the ecosystem for the sustainable development of human beings. However, the studies focusing on grass identification, which were traditionally implemented by experts with low efficiency and precision, cannot meet the requirements of modern grassland ma...

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Main Authors: Fan Han, Xue Qiao, Yubao Ma, Weihong Yan, Xinyu Wang, Xin Pan
Format: Article
Language:English
Published: Wiley 2020-01-01
Series:Advances in Multimedia
Online Access:http://dx.doi.org/10.1155/2020/1909875
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author Fan Han
Xue Qiao
Yubao Ma
Weihong Yan
Xinyu Wang
Xin Pan
author_facet Fan Han
Xue Qiao
Yubao Ma
Weihong Yan
Xinyu Wang
Xin Pan
author_sort Fan Han
collection DOAJ
description Grass is one of the most important resources in the ecosystem for the sustainable development of human beings. However, the studies focusing on grass identification, which were traditionally implemented by experts with low efficiency and precision, cannot meet the requirements of modern grassland management. In this study, we proposed cubic interpolation LBP (CILBP) and dbN wavelets for grass identification based on leaf images. A low-frequency component of leaf images decomposed by dbN wavelets was used as the input of CILBP for more subtle texture extraction. The novelty of the proposed method was that CILBP can better describe the texture features from the low-frequency subimage, as compared with the original bilinear LBP. The effectiveness in identification accuracy of the proposed method for grass leaf was demonstrated by the experimental results.
format Article
id doaj-art-231adbcd598143aea16157fdb9ea3849
institution OA Journals
issn 1687-5680
1687-5699
language English
publishDate 2020-01-01
publisher Wiley
record_format Article
series Advances in Multimedia
spelling doaj-art-231adbcd598143aea16157fdb9ea38492025-08-20T02:04:35ZengWileyAdvances in Multimedia1687-56801687-56992020-01-01202010.1155/2020/19098751909875Grass Leaf Identification Using dbN Wavelet and CILBPFan Han0Xue Qiao1Yubao Ma2Weihong Yan3Xinyu Wang4Xin Pan5College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaInstitute of Grassland Research of CAAS, Inner Mongolia, Hohhot 010020, ChinaInstitute of Grassland Research of CAAS, Inner Mongolia, Hohhot 010020, ChinaCollege of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaCollege of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot 010018, ChinaGrass is one of the most important resources in the ecosystem for the sustainable development of human beings. However, the studies focusing on grass identification, which were traditionally implemented by experts with low efficiency and precision, cannot meet the requirements of modern grassland management. In this study, we proposed cubic interpolation LBP (CILBP) and dbN wavelets for grass identification based on leaf images. A low-frequency component of leaf images decomposed by dbN wavelets was used as the input of CILBP for more subtle texture extraction. The novelty of the proposed method was that CILBP can better describe the texture features from the low-frequency subimage, as compared with the original bilinear LBP. The effectiveness in identification accuracy of the proposed method for grass leaf was demonstrated by the experimental results.http://dx.doi.org/10.1155/2020/1909875
spellingShingle Fan Han
Xue Qiao
Yubao Ma
Weihong Yan
Xinyu Wang
Xin Pan
Grass Leaf Identification Using dbN Wavelet and CILBP
Advances in Multimedia
title Grass Leaf Identification Using dbN Wavelet and CILBP
title_full Grass Leaf Identification Using dbN Wavelet and CILBP
title_fullStr Grass Leaf Identification Using dbN Wavelet and CILBP
title_full_unstemmed Grass Leaf Identification Using dbN Wavelet and CILBP
title_short Grass Leaf Identification Using dbN Wavelet and CILBP
title_sort grass leaf identification using dbn wavelet and cilbp
url http://dx.doi.org/10.1155/2020/1909875
work_keys_str_mv AT fanhan grassleafidentificationusingdbnwaveletandcilbp
AT xueqiao grassleafidentificationusingdbnwaveletandcilbp
AT yubaoma grassleafidentificationusingdbnwaveletandcilbp
AT weihongyan grassleafidentificationusingdbnwaveletandcilbp
AT xinyuwang grassleafidentificationusingdbnwaveletandcilbp
AT xinpan grassleafidentificationusingdbnwaveletandcilbp