Tree inspection system, tree inspection method, and program

Claims

1. An acquisition means for acquiring an image and location information of the location where the image was taken, A recognition means for recognizing street trees from the aforementioned image using image recognition, A measuring means for measuring at least one of the color of the area of ​​the street trees in the image or the bias of the area of ​​the street trees in the image, A determination means for determining the health of the street trees based on at least one of the distribution of the aforementioned colors or the aforementioned bias, Output means that associates the location information with the results of the determination of the health of the street trees and outputs the results. A tree inspection system equipped with the following features.

2. The aforementioned color distribution is the luminance distribution of at least the green component of the RGB values ​​of each pixel in the area of ​​the street trees. The tree inspection system according to claim 1.

3. The determination means determines that the street trees are healthy if the proportion of pixels with a green component brightness greater than the threshold is large. The tree inspection system according to claim 2.

4. The determination means determines the health of the street tree based on at least one of the proportion of green pixels or the proportion of orange pixels included in the area of ​​the street tree. A tree inspection system according to any one of claims 1 to 3.

5. The determination means determines that the street tree is healthy if the similarity between the statistically processed RGB values ​​of each pixel in the area of ​​the street tree and the value representing the color green is higher than the standard. A tree inspection system according to any one of claims 1 to 3.

6. The aforementioned bias is the inclination in the image of the rectangle having the smallest area in contact with the street tree in the image. A tree inspection system according to any one of claims 1 to 3.

7. The recognition means recognizes a rectangular area surrounding the street tree by object detection, with sides parallel to the sides of the image. The aforementioned bias is represented by the aspect ratio of the recognized rectangular region. A tree inspection system according to any one of claims 1 to 3.

8. The recognition means recognizes whether each pixel of the image represents a street tree or not. The aforementioned bias is represented by the left-right ratio of the number of pixels representing the street trees when the area of ​​the street trees is divided by a straight line. A tree inspection system according to any one of claims 1 to 3.

9. The image and the location information of the place where the image was taken are obtained. Street trees are recognized from the aforementioned image using image recognition. The color of the area of ​​the street trees in the aforementioned image or the bias of the area of ​​the street trees in the aforementioned image is measured. Based on at least one of the distribution of the aforementioned colors or the aforementioned bias, the health of the street trees is determined. The location information and the result of the health assessment of the street trees are linked and output. Tree inspection methods.

10. The image and the location information of the place where the image was taken are obtained. Street trees are recognized from the aforementioned image using image recognition. The color of the area of ​​the street trees in the aforementioned image or the bias of the area of ​​the street trees in the aforementioned image is measured. Based on at least one of the distribution of the aforementioned colors or the aforementioned bias, the health of the street trees is determined. The location information and the result of the health assessment of the street trees are linked and output. A program that instructs a computer to perform a process.