Point Clouds Classification Algorithm of Vegetation Based on Area and Pointing Features

Zhouyang Hua; Sheng Xu; Ying’an Liu

doi:10.3788/LOP202259.1828001

Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 18 >Page 1828001 > Article

Laser & Optoelectronics Progress
Vol. 59, Issue 18, 1828001 (2022)

Point Clouds Classification Algorithm of Vegetation Based on Area and Pointing Features

Zhouyang Hua, Sheng Xu, and Ying’an Liu^*

Author Affiliations

College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, Jiangsu , China

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DOI: 10.3788/LOP202259.1828001 Cite this Article Set citation alerts

Zhouyang Hua, Sheng Xu, Ying’an Liu. Point Clouds Classification Algorithm of Vegetation Based on Area and Pointing Features[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1828001 Copy Citation Text

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Fig. 1. Experimental flow chart

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Fig. 2. Data_1 preprocessing picture

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Fig. 3. Data_2 preprocessing picture

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Fig. 4. Relationship between the number of input features and the change of corresponding precision

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Fig. 5. Weight corresponding to each feature

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Fig. 6. Renderings of Data_1 before (left) and after (right) using the new features. (a) Trees; (b) ground; (c) bushes

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Fig. 7. Renderings of Data_2 before (left) and after (right) using the new features. (a) Trees; (b) ground

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Name		Combination value	Name		Combination value
∑_λ	Sum	$λ_{1} + λ_{2} + λ_{3}$	C_λ	Surface Variation	$\frac{λ_{3}}{λ_{1} + λ_{2} + λ_{3}}$
O_λ	Omnivariance	$\sqrt[3]{λ_{1} \cdot λ_{2} \cdot λ_{3}}$	S_λ	Sphericity	$\frac{λ_{3}}{λ_{1}}$
A_λ	Anisotropy	$\frac{λ_{1} - λ_{3}}{λ_{1}}$	V_λ	Verticality	$1 - \|〈[\begin{matrix} 0 & 0 & 1 \end{matrix}], e_{3}〉\|$
P_λ	Planarity	$\frac{λ_{2} - λ_{3}}{λ_{1}}$	J_λ	Area	$\frac{λ_{1} \cdot λ_{2}}{λ_{3}}$
L_λ	Linearity	$\frac{λ_{1} - λ_{2}}{λ_{1}}$	Z_λ	Pointing	$\frac{λ_{3} \cdot λ_{1}}{λ_{2}}$

Table 1. Feature combination

Feature	Recall /%		Precision /%		F1-Score /%		Accuracy /%
Feature	Data_1	Data_2	Data_1	Data_2	Data_1	Data_2	Data_1	Data_2
A_λ、P_λ、L_λ、S_λ、V_λ	33.33	79.26	56.90	90.39	42.04	84.46	56.90	84.88
λ₁、λ₂、λ₃、∑_λ、O_λ	66.62	99.48	99.02	99.33	79.65	99.41	99.14	99.51
λ₁、λ₂、λ₃、∑_λ、O_λ、A_λ、P_λ	66.78	99.50	99.35	99.35	79.88	99.43	99.15	99.52
λ₁、λ₂、λ₃、∑_λ、O_λ、J_λ、Z_λ	97.79	99.80	99.93	99.65	98.85	99.72	99.90	99.74

Table 2. Accuracy analysis of vegetation classification

Algorithm	Recall /%		Precision /%		F1-Score /%		Accuracy /%
Algorithm	Data_1	Data_2	Data_1	Data_2	Data_1	Data_2	Data_1	Data_2
UXWFF	99.07	97.57	83.80	96.10	90.79	96.83	98.65	96.92
MCM	66.67	66.19	99.06	98.16	79.69	79.07	99.19	98.39
PCCM	99.01	99.09	98.34	98.46	98.68	98.77	98.75	98.84
Proposed algorithm	97.79	99.80	99.93	99.65	98.85	99.72	99.90	99.74

Table 3. Quantitative comparison between proposed algorithm and other algorithms on Data _1 and Data_ 2

Zhouyang Hua, Sheng Xu, Ying’an Liu. Point Clouds Classification Algorithm of Vegetation Based on Area and Pointing Features[J]. Laser & Optoelectronics Progress, 2022, 59(18): 1828001

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