Intelligent evaluation of grotto surface weathering based on spectral chromatic aberration and principal component feature fusion

Chi-peng CAO; Hui-qin WANG; Ke WANG; Zhan WANG; Gang ZHANG; Tao MA

doi:10.37188/OPE.20212910.2444

Optics and Precision Engineering, Volume. 29, Issue 10, 2444(2021)

Intelligent evaluation of grotto surface weathering based on spectral chromatic aberration and principal component feature fusion

Chi-peng CAO1... Hui-qin WANG1,*, Ke WANG1, Zhan WANG2, Gang ZHANG2 and Tao MA2 |Show fewer author(s)

Author Affiliations

¹School of Information and Control Engineering， Xi'an University of Architecture and Technology， Xi'an70055， China

²Shanxi Provincial Institute of Cultural Relics Protection， Xi’an710075， China

show less

Abstract Get PDF(in Chinese)

Figures & Tables(13)

Fig. 1. Reflection spectrum characterization of different weathering types and degrees on the surface of grotto

Download full size

View in Article

Fig. 2. Multi-spectral imaging data of weathering area on the surface of grotto

Download full size

View in Article

Fig. 3. Technical block diagram of intelligent evaluation method for grotto surface weathering

Download full size

View in Article

Fig. 4. Reconstructed spectral characteristic curve of grotto surface

Download full size

View in Article

Fig. 5. Principal component analysis results of multi-spectral image of cave surface weathering

Download full size

View in Article

Fig. 6. Principal component analysis results image color image image

Download full size

View in Article

Fig. 7. Overall evaluation results of weathering on the surface of grotto

Download full size

View in Article

Table 1. Changes of Lab， XYZ and RGB in different weathering types and weathering degree areas

View table

View in Article

Table 1. Changes of Lab， XYZ and RGB in different weathering types and weathering degree areas

Weathering type	$W_{s t r o n g 1}$	$W_{s t r o n g 2}$	$W_{w e a k 1}$	$W_{w e a k 2}$	$W_{s l i g h t l y 1}$	$W_{s l i g h t l y 2}$	$W_{d u s t 1}$	$W_{d u s t 2}$
L*	46.4	43.7	42.6	37.7	33.0	28.0	8.0	7.9
a*	3.5	4.7	3.5	3.1	3.6	2.5	0.2	0.2
b*	8.9	10.5	8.3	8.7	9.0	7.6	7.9	7.8
X	15.7	13.9	13.0	10.0	7.7	5.5	0.8	0.8
Y	15.6	13.6	12.9	9.9	7.5	5.5	0.9	0.9
Z	9.8	8.1	8.1	6.0	4.4	3.2	0.3	0.3
R	121	117	111	98	88	74	27	27
G	108	100	98	87	75	64	23	23
B	95	85	86	74	63	55	10	10

Table 2. Color difference judgment standard
View table
View in Article
Table 2. Color difference judgment standard
$Δ E$ Chromatic aberration degree identification
0~0.5 Trace
0.5~1.5 Lightweight
1.5~3.0 Can feel
3.0~6.0 obvious
6.0~12.0 tremendous
$\geq$ 12.0 huge

Table 3. Color difference between different weathering types and weathering degrees and reference points
View table
View in Article
Table 3. Color difference between different weathering types and weathering degrees and reference points
Color difference type $W_{s t r o n g} - W_{b e n c h m a r k}$ $W_{w e a k} - W_{b e n c h m a r k}$ $W_{s l i g h t l y} - W_{b e n c h m a r k}$ $W_{d u s t} - W_{b e n c h m a r k}$
$Δ E$ 76 45.19 38.81 29.12 11.24
$Δ E$ 94 45.19 38.81 29.12 11.24
$Δ E$ 2 000 32.37 27.01 19.57 8.2

Table 4. Color difference between different weathering types and degrees
View table
View in Article
Table 4. Color difference between different weathering types and degrees
Color difference type $W_{s t r o n g}$ $W_{w e a k}$ $W_{s l i g h t l y}$ $W_{d u s t}$ $W_{b e n c h m a r k}$
$W_{s t r o n g}$ 0 5.83 12.68 21.01 74.05
$W_{w e a k}$ 5.83 0 6.85 5.83 68.22
$W_{s l i g h t l y}$ 12.68 6.85 0 8.33 61.37
$W_{d u s t}$ 21.01 15.18 8.33 0 53.04
$W_{b e n c h m a r k}$ 74.05 68.22 61.37 53.04 0

Table 5. Contribution rate and cumulative contribution rate of the first three principal components
View table
View in Article
Table 5. Contribution rate and cumulative contribution rate of the first three principal components
Principal component Eigenvalues Contribution rate Cumulative contribution rate
PC1 16757.90 95.41% 95.41%
PC2 579.80 3.30% 98.71%
PC3 92.21 0.53% 99.24%

Table 6. Comparison of accuracy and kappa coefficient of four evaluation methods

View table

View in Article

Table 6. Comparison of accuracy and kappa coefficient of four evaluation methods

Method	Accuracy evaluation	Color difference-principal component	Reflectance spectrum	principal component	Color difference
RF	Training accuracy	100.00%	99.91%	98.52%	93.03%
	Prediction accuracy	99.86%	98.49%	91.34%	70.26%
	Kappa coefficient	0.99	0.98	0.89	0.53
KNN	Training accuracy	99.79%	94.99%	88.60%	75.43%
	Prediction accuracy	97.50%	91.69%	82.68%	66.84%
	Kappa coefficient	0.96	0.90	0.69	0.42
BP	Training accuracy	63.93%	63.19%	46.13%	36.84%
	Prediction accuracy	50.81%	48.00%	42.19%	32.51%
	Kappa coefficient	0.28	0.25	0.21	0.18
RBF	Training accuracy	96.12%	95.95%	87.52%	70.08%
	Prediction accuracy	94.73%	92.88%	85.96%	65.84%
	Kappa coefficient	0.92	0.91	0.75	0.39

Tools

Get Citation

Copy Citation Text

Chi-peng CAO, Hui-qin WANG, Ke WANG, Zhan WANG, Gang ZHANG, Tao MA. Intelligent evaluation of grotto surface weathering based on spectral chromatic aberration and principal component feature fusion[J]. Optics and Precision Engineering, 2021, 29(10): 2444

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Information Sciences

Received: Feb. 9, 2021

Accepted: --

Published Online: Nov. 23, 2021

The Author Email: WANG Hui-qin (hqwang@xauat.edu.cn)

DOI:10.37188/OPE.20212910.2444

Topics

laser devices and laser physics

Lasers and Laser Optics

Laser physics

laser manufacturing

Instrumentation, Measurement and Metrology

Table 1. Changes of L*a*b， XYZ and RGB in different weathering types and weathering degree areas

Table 1. Changes of L*a*b， XYZ and RGB in different weathering types and weathering degree areas

Table 2. Color difference judgment standard

Table 2. Color difference judgment standard

Table 3. Color difference between different weathering types and weathering degrees and reference points

Table 3. Color difference between different weathering types and weathering degrees and reference points

Table 4. Color difference between different weathering types and degrees

Table 4. Color difference between different weathering types and degrees

Table 5. Contribution rate and cumulative contribution rate of the first three principal components

Table 5. Contribution rate and cumulative contribution rate of the first three principal components

Table 6. Comparison of accuracy and kappa coefficient of four evaluation methods

Table 6. Comparison of accuracy and kappa coefficient of four evaluation methods

微信扫一扫：分享

Table 1. Changes of Lab， XYZ and RGB in different weathering types and weathering degree areas

Table 1. Changes of Lab， XYZ and RGB in different weathering types and weathering degree areas