US 2022/0189033 A1Published application

Boundary detection device and method thereof

AssigneeULSee Inc.

InventorYi-Ta WU

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Abstract

A boundary detection device is provided in the present invention. The boundary detection device includes a camera drone and an image processing unit. The camera drone, for shooting a region to obtain an aerial image data. The image processing unit is configured to convert the aerial image data from a RGB color space to an XYZ color space, then convert the aerial image data from the XYZ color space to a Lab color space to obtain a Lab color image data, and then operate a brightness feature data and a color feature data according to the Lab color image data. The image processing unit picks first to eighth circular masks, each of the circular masks having a boundary line to divide the mask region into two left and right semicircles with different colors.

Claims10

Dependent claims

A boundary detection device, comprising:

a camera drone, for shooting a region to obtain an aerial image data;
an image processing unit, communicatively connected to the camera drone, wherein the image processing unit is configured to convert the aerial image data from a RGB color space to an XYZ color space according to a formula
[
X
Y
Z
]
=
[
0.4124
0
.
3
⁢
5
⁢
7
⁢
5
0.1804
0.2126
0.7151
0
.
0
⁢
721
0.0193
0.1191
0
.
9
⁢
5
⁢
0
⁢
2
]
⁢
[
R
G
B
]
,
then convert the aerial image data from the XYZ color space to a Lab color space according to a formula:
L
=
{
116
*
(
Y
Y
n
)
1
3
-
16
,
if
⁢
⁢
Y
Y
n
>
0
.
0
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0
⁢
8
⁢
8
⁢
5
⁢
6
9.03
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.3
*
Y
Y
n
,
others
⁢
⁢
a
=
5
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0
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(
f
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(
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X
n
)
-
f
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(
Y
Y
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)
)
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b
=
200
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(
f
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(
Y
Y
n
)
-
f
⁡
(
Z
Z
n
)
)
⁢
⁢
wherein
⁢
⁢
X
n
=
0
.
9
⁢
515
⁢
⁢
Y
n
=
1.0000
⁢
⁢
Z
n
=
1.0886
⁢
⁢
f
⁡
(
t
)
=
{
t
1
3
,
⁢
if
⁢
⁢
t
>
0.0
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6
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t
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6
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6
,
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others
to obtain a Lab color image data, and then operate a brightness feature data and a color feature data according to the Lab color image data;
then, the image processing unit picks first to eighth circular masks, each of the circular masks having a boundary line to divide the mask region into two left and right semicircles with different colors, and boundary lines of the first to eighth circular masks are separated from a boundary line of the first circular shield by 22.5° clockwise in sequence;
the image processing unit employs the first to eighth circular masks to perform a light and shadow intensity operation on each image point in the Lab color image data to obtain a texture feature data;
and
the image processing unit performs operations according to the brightness feature data, the color feature data, and the texture feature data to obtain a first image boundary contour data.

213 more elements

A boundary detection method, comprising steps of:

(1) shooting a region to obtain an aerial image data with a camera drone, and sending the aerial image data to an image processing unit;
(2) converting, with the image processing unit, the aerial image data from a RGB color space to an XYZ color space according to a formula
[
X
Y
Z
]
=
[
0.4124
0
.
3
⁢
5
⁢
7
⁢
5
0.1804
0.2126
0.7151
0
.
0
⁢
721
0.0193
0.1191
0
.
9
⁢
5
⁢
0
⁢
2
]
⁢
[
R
G
B
]
,
then convert the aerial image data from the XYZ color space to a Lab color space according to a formula:
L
=
{
116
*
(
Y
Y
n
)
1
3
-
16
,
if
⁢
⁢
Y
Y
n
>
0
.
0
⁢
0
⁢
8
⁢
8
⁢
5
⁢
6
9.03
⁢
.3
*
Y
Y
n
,
others
⁢
⁢
a
=
5
⁢
0
⁢
0
*
(
f
⁡
(
X
X
n
)
-
f
⁡
(
Y
Y
n
)
)
⁢
⁢
b
=
200
*
(
f
⁡
(
Y
Y
n
)
-
f
⁡
(
Z
Z
n
)
)
⁢
⁢
wherein
⁢
⁢
X
n
=
0
.
9
⁢
515
⁢
⁢
Y
n
=
1.0000
⁢
⁢
Z
n
=
1.0886
⁢
⁢
f
⁡
(
t
)
=
{
t
1
3
,
⁢
if
⁢
⁢
t
>
0.0
⁢
0
⁢
8
⁢
8
⁢
5
⁢
6
7.787
*
t
+
1
⁢
6
1
⁢
1
⁢
6
,
⁢
others
;
(3) operating, with the image processing unit, a brightness feature data and a color feature data according to the Lab color image data;
(4) picking, with the image processing unit, first to eighth circular masks, each of the circular masks having a boundary line to divide the mask region into two left and right semicircles with different colors, wherein boundary lines of the first to eighth circular masks are separated from a boundary line of the first circular shield by 22.5° clockwise in sequence;
employing, with the image processing unit, the first to eighth circular masks to perform a light and shadow intensity operation on each image point in the Lab color image data to obtain a texture feature data;
and
(5) performing, with the image processing unit, operations according to the brightness feature data, the color feature data, and the texture feature data to obtain a first image boundary contour data.

214 more elements

Dependencies are inferred from the claim text.

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Abstract