A Lawn Deterioration Model Constructed from Image Data Yurie Enomoto, Chisato Ishikawa, Masami...
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A Lawn Deterioration Model Constructed from Image Data Yurie Enomoto, Chisato Ishikawa, Masami Takata, Kazuki Joe Department of Advanced Information & Computer Sciences, Nara Women’s University, Nara, Japan
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3 Background Periodical mowing →Affect the quality of lawns Necessity of a model to understand the relation between the durability of lawns color and the paint density Keep the quality of lawns Improve just color of lawns →Green paint spraying on the lawn with degraded leaf color ~Advantage~ A low cost technique Simple operations BeforeAfter
Transcript of A Lawn Deterioration Model Constructed from Image Data Yurie Enomoto, Chisato Ishikawa, Masami...
A Lawn Deterioration Model Constructed from Image Data
Yurie Enomoto, Chisato Ishikawa, Masami Takata, Kazuki JoeDepartment of Advanced Information & Computer Sciences,
Nara Women’s University, Nara, Japan
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Contents
BackgroundImage Analysis for Lawns Sprayed with Paint
Analysis by RGB and Model ConstructionAnalysis by HSV and Model Construction
Image Analysis for Lawns Sprinkled with WaterAnalysis by RGB and Model ConstructionAnalysis by HSV and Model Construction
Conclusions and Future works
3
BackgroundPeriodical mowing→Affect the quality of lawns
Necessity of a model to understand the relationbetween the durability of lawns color and the paint density
Keep the quality of lawns
Improve just color of lawns →Green paint spraying on the lawn with degraded leaf color
~Advantage~ A low cost technique Simple operations
Before After
4
Lawn Images
For deterioration models of lawns sprayed with paint
1) Before spraying paint 2) Just after spraying paint 3) 40 minutes later
4) 8 days later 5) 11 days later ① 6) 11 days later ②
5
Lawn Images
For deterioration model of water-sprinkled lawns
1) Right after water-sprinkled (3 pieces)
2) 8 days later (3 pieces) 3) 16 days later (3 pieces)
4) 21 days later (3 pieces) 5) 28 days later (3 pieces)
6
Image Analysis for Lawns Sprayed with Paint
Pixel value in the top of graph （ Central value ） →The maximum number of pixelsThe width from the central value (Dispersion width)
→The dispersion of density value
020040060080010001200140016001800
0 50 100 150 200 250Pixel value
The
num
ber
of p
ixel v
alue
RGB
RGB values Gaussian distribution
7
Analysis by dispersion widths of RGB
05
10152025303540
(ⅰ )Beforespraying
paint
(ⅱ )J ustafter
sprayingpaint
(ⅲ )40minutes
later
(ⅳ)8 dayslater
ⅴ )11（days later
①
(ⅵ)11days later
②
Disp
ersi
on w
idth
Ｒ
Ｇ
Ｂ
Image Analysis for Lawns Sprayed with Paint
8
＜ After 8 days ＞R ・ B ： Expansion of dispersion → Degradation of the lawns
Analysis by dispersion widths of RGB
05
10152025303540
(ⅰ )Beforespraying
paint
(ⅱ )J ustafter
sprayingpaint
(ⅲ )40minutes
later
(ⅳ)8 dayslater
ⅴ )11（days later
①
(ⅵ)11days later
②
Disp
ersio
n wi
dth
Ｒ
Ｇ
Ｂ
Image Analysis for Lawns Sprayed with Paint
9
＜ After 8 days ＞R ・ B ： Expansion of dispersion → Degradation of the lawnsG ： Smaller dispersion than R,B → Controlled deterioration of lawns color
Analysis by dispersion widths of RGB
05
10152025303540
(ⅰ )Beforespraying
paint
(ⅱ )J ustafter
sprayingpaint
(ⅲ )40minutes
later
(ⅳ)8 dayslater
ⅴ )11（days later
①
(ⅵ)11days later
②
Disp
ersio
n wi
dth
Ｒ
Ｇ
Ｂ
Image Analysis for Lawns Sprayed with Paint
10
Model Construction ＜Ｒ・Ｂ＞（ 1 ）
（ 2 ）
axe11
f(x)
1xaxf(x) 2
2
Increase to a certain value to converge
Sigmoid function
A fractional function
a: 1.5a: 1.0a: 0.5
a: 0.5a: 1.0a: 1.5
11
Model Construction ＜Ｒ・Ｂ＞
R ： x5.2e11
f(x) B ：
1xx30f(x) 2
2
30
28
24
26
20
22
18
16
26
24
22
20
18
16
14
28
Analysis result by RModel expression for R
Analysis result by BModel expression for B
12
Model Construction ＜Ｇ＞
2xalogxf(x))3(
2x2eaxf(x))4(
2bxaxef(x))5(
A function with a peak of enlarged dispersion
Change by coefficient a Change by coefficient b
Expression(3):Logarithm based functionExpression(4)(5):Exponential based function
a: 5a: 10a: 15
a: 0.5a: 1.0a: 1.5
a: 0.5, b: 1.0a: 1.0, b: 1.0a: 1.5, b: 1.0
a: 1.0, b: 0.5a: 1.0, b: 1.0a: 1.0, b: 1.5
13
Model Construction ＜Ｇ＞
2xalogxf(x))3(
2x2eaxf(x))4(
2bxaxef(x))5(
A function with a peak of enlarged dispersion
Change by coefficient a Change by coefficient b
Expression(3):Logarithm based functionExpression(4)(5):Exponential based function
G ： 2x1.0xe20f(x)
a: 5a: 10a: 15
a: 0.5a: 1.0a: 1.5
a: 0.5, b: 1.0a: 1.0, b: 1.0a: 1.5, b: 1.0
a: 1.0, b: 0.5a: 1.0, b: 1.0a: 1.0, b: 1.5
28262422201816
Analysis result by GModel expression for G
14
Image Analysis for Lawns Sprayed with PaintAnalysis by dispersion widths of HSV
01020304050607080
(i)Beforespraying
paint
(ii)J ustafter
sprayingpaint
(iii)40minutes
later
(iv)8dayslater
(v)11days
later①
(vi)11days
later②
Disp
ersio
n wi
dth
HSV
15
Analysis by dispersion widths of HSV
01020304050607080
(i)Beforespraying
paint
(ii)J ustafter
sprayingpaint
(iii)40minutes
later
(iv)8dayslater
(v)11days
later①
(vi)11days
later②
Disp
ersio
n wi
dth
HSV
H : Expansion of dispersion
→Expansion of the range of green in the hue circle
→ Increase of the number of color hue
Image Analysis for Lawns Sprayed with Paint
16
Analysis by dispersion widths of HSV
01020304050607080
(i)Beforespraying
paint
(ii)J ustafter
sprayingpaint
(iii)40minutes
later
(iv)8dayslater
(v)11days
later①
(vi)11days
later②
Disp
ersio
n wi
dth
HSV
H : Expansion of dispersion
→Expansion of the range of green in the hue circle
→Increase of the number of color hue
S ・ V : Expansion of dispersion 8 days later
→Dark lawns color
Image Analysis for Lawns Sprayed with Paint
17
Model Construction ＜ H ・ S ・ V ＞axe1
1f(x)
1xaxf(x) 2
2
（1）
（2）
01020304050607080
(i)Beforespraying
paint
(ii)J ustafter
sprayingpaint
(iii)40minutes
later
(iv)8dayslater
(v)11days
later①
(vi)11days
later②
Disp
ersio
n wi
dth
HSV
※p.9
a: 1.5a: 1.0a: 0.5
a: 0.5a: 1.0a: 1.5
18
Model Construction ＜ H ・ S ・ V ＞
S ： x5.1e11
f(x) H ：
1xx65f(x) 2
2
V ： x7.0e1
1f(x)
6055504540353025
5654525048464442
484644
42
4038
36
3432
Analysis result by HModel expression for H
Analysis result by SModel expression for S
Analysis result by VModel expression for V
19
Fresh (green) part
RGB values
02000400060008000
1000012000140001600018000
1 17 33 49 65 81 97 113
129
145
161
177
193
209
225
241
Pixel value
The
num
ber
of p
ixel
val
ue
Dried-up (white) part Analysis
Image Analysis for Lawns Sprinkled with Water
Binomial distribution
20
RGB： Expansion of dispersion from 8 days later to 16 days later→Quick deterioration of green part→Gentle gradient of Gaussian distributionR ： The most deterioration
Analysis by dispersion widths of RGB
0
10
20
30
40
50
60
70
(i)Rightafter water-
sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersi
on w
idth
RGB
Image Analysis for Lawns Sprinkled with Water
21
Model Construction ＜ R ・ G ・ B ＞axe1
1f(x)
1xaxf(x) 2
2
（1）
（2）
0
10
20
30
40
50
60
70
(i)Rightafter water-
sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersi
on w
idth
RGB
※p.9
a: 0.5a: 1.0a: 1.5
a: 1.5a: 1.0a: 0.5
22
Model Construction ＜ R ・ G ・ B ＞
G ： x2e11
f(x) R ： B ： x5.2e1
1f(x)
x3e11
f(x)
70
60
50
40
30
20
10
2826242220181614
6055
50454035
30
25
20
Analysis result by RModel expression for R
Analysis result by GModel expression for G
Analysis result by BModel expression for B
23
Analysis by dispersion widths of HSV
0
10
20
30
40
50
60
(i)Right afterwater-
sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersio
n wi
dth
HSV
Image Analysis for Lawns Sprinkled with Water
24
H ・ S ： Reduction of dispersion 8 days later →Dispersion on green and yellow part
Analysis by dispersion widths of HSV
0102030405060
(i)Rightafter
water-sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersi
on w
idth
HSV
Image Analysis for Lawns Sprinkled with Water
25
H ・ S ： Reduction of dispersion 8 days later →Dispersion on green and yellow partV： Expansion of dispersion →Deterioration of green part →Gentle gradient of Gaussian distribution
Analysis by dispersion widths of HSV
0102030405060
(i)Rightafter
water-sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersi
on w
idth
HSV
Image Analysis for Lawns Sprinkled with Water
26
Model Construction ＜ V ＞axe1
1f(x)
1xaxf(x) 2
2
（1）
（2）
0102030405060
(i)Rightafter
water-sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersion
width
HSV
※p.9
a: 0.5a: 1.0a: 1.5
a: 1.5a: 1.0a: 0.5
27
Model Construction ＜ V ＞
V：
0
10
20
30
40
50
60
(i)Right afterwater-
sprinkled
(ii)8 dayslater
(iii)16 dayslater
(iv)21 dayslater
(v)28 dayslater
Disp
ersio
n wi
dth
HSV
1xx49f(x) 2
2
50
45
40
35
30
25
20
Analysis result by VModel expression for V
28
Model Construction ＜ H ・ S ＞
bx
axf(x))6(
0,0axf(x))7( b ba
Change by coefficient a Change by coefficient b
Change by coefficient a Change by coefficient b
Decrease by a certain valueto converge
Expression(6):
Exponential based function
Expression(7):
A decreasing function
a: 0.5, b: -0.5a: 1.0, b: -0.5a: 1.5, b: -0.5
a: 1.5, b: -0.5a: 1.5, b: -1.0a: 1.5, b: -1.5
a: 5, b: 5a: 10, b: 5a: 15, b: 5
a: 0.5, b: 5a: 0.5, b: 10a: 0.5, b: 15
29
Model Construction ＜ H ・ S ＞
H ： S ：2.0x93f(x) 5.4x160f(x)x
95
90
85
80
75
70
65
130
120
110
100
9080
70
50
60
4030
Analysis result by HModel expression for H
Analysis result by SModel expression for S
30
Conclusions and Future WorksConstruct lawn deterioration models by image data
Future work More exact model construction by aggregate of a botanical model
<Model for G>
Sprinkled with waterSprayed with paint
60
50
40
30
20
10
Difference 35
31
Thank you for your attention.
