Grass detection device and method thereof
AssigneeULSee Inc.
InventorYi-Ta WU
Life of this patent
Estimating the term…
Abstract
A grass detection device is provided in the present invention. The grass detection device includes a camera drone and an image processing unit. The camera drone, for shooting an area to obtain an aerial image data. The image processing unit is configured to perform binarization operations on the aerial image data to finally obtain a grass ground binarization image data, and then compare the aerial image data with the grass ground binarization image data for marking a part of the aerial image data that belongs to the grass ground to finally obtain a grass detection image data.
Claims10
A grass detection device, comprising:
- a camera drone, for shooting an area to obtain an aerial image data;
- an image processing unit, communicatively connected to the camera drone, wherein the image processing unit is configured to perform binarization operations on the aerial image data according to a formula as below:
- H
- =
- {
- θ
- G
- ≥
- B
- 360
- -
- θ
- G
- ≤
- B
-
-
- S
- =
- 1
- -
- 3
- R
- +
- G
- +
- B
-
- [
- min
-
- (
- R
- ,
- G
- ,
- B
- )
- ]
-
-
- V
- =
- 1
- 3
-
- (
- R
- +
- G
- +
- B
- )
-
-
- θ
- =
- cos
- -
- 1
-
- {
- 2
-
- R
- -
- G
- -
- B
- 2
-
- (
- R
- -
- G
- )
- 2
- +
- (
- R
- -
- B
- )
-
- (
- G
- -
- B
- )
- }
-
-
- Image
- =
- Image_H
- ⊗
- Image_S
- ⊗
- Image_I
- ,
- and
-
-
- {
- Image
-
- (
- x
- ,
- y
- )
-
- =
- 1
-
- ,
- H
- ∈
- [
- 0
-
- .2
-
- ,
- 0.45
- ]
- ,
- S
- ∈
- [
- 0.2
- ,
- 0.65
- ]
- ,
- I
- ∈
- [
- 0
- .
- 2
-
- 5
-
- ,
- 1
- ]
- Image
-
- (
- x
- ,
- y
- )
-
- =
- 0
- ,
- others
- ,
- to finally obtain a grass ground binarization image data, and then compare the aerial image data with the grass ground binarization image data for marking a part of the aerial image data that belongs to the grass ground to finally obtain a grass detection image data.
A grass detection method, comprising steps of:
- (1) shooting a region to obtain an aerial image data with a camera drone;
- (2) performing, with the image processing unit, binarization operations on the aerial image data according to a formula as below:
- H
- =
- {
- θ
- G
- ≥
- B
- 360
- -
- θ
- G
- ≤
- B
-
-
- S
- =
- 1
- -
- 3
- R
- +
- G
- +
- B
-
- [
- min
-
- (
- R
- ,
- G
- ,
- B
- )
- ]
-
-
- V
- =
- 1
- 3
-
- (
- R
- +
- G
- +
- B
- )
-
-
- θ
- =
- cos
- -
- 1
-
- {
- 2
-
- R
- -
- G
- -
- B
- 2
-
- (
- R
- -
- G
- )
- 2
- +
- (
- R
- -
- B
- )
-
- (
- G
- -
- B
- )
- }
-
-
- Image
- =
- Image_H
- ⊗
- Image_S
- ⊗
- Image_I
- ,
- and
-
-
- {
- Image
-
- (
- x
- ,
- y
- )
-
- =
- 1
-
- ,
- H
- ∈
- [
- 0
-
- .2
-
- ,
- 0.45
- ]
- ,
- S
- ∈
- [
- 0.2
- ,
- 0.65
- ]
- ,
- I
- ∈
- [
- 0
- .
- 2
-
- 5
-
- ,
- 1
- ]
- Image
-
- (
- x
- ,
- y
- )
-
- =
- 0
- ,
- others
- ,
- finally obtaining a grass ground binarization image data;
- and
- (3) comparing, with the image processing unit, the aerial image data with the grass ground binarization image data for marking a part of the aerial image data that belongs to the grass ground to finally obtain a grass detection image data.
Dependencies are inferred from the claim text.