US 2020/0051180 A1 · CROP DISEASE RECOGNITION AND YIELD ESTIMATION

Abstract

In an embodiment, a computer-implemented method is disclosed. The method comprises causing a camera to continuously capture surroundings to generate multiple images and causing a display device to continuously display the multiple images as the multiple images are generated. In addition, the method comprises processing each of one or more of the multiple images. The processing comprises identifying at least one of a plurality of diseases and calculating at least one disease score associated with the at least one disease for a particular image; causing the display device to display information regarding the at least one disease and the at least one disease score in association with a currently displayed image; receiving input specifying one or more of the at least one disease; and causing the display device to show additional data regarding the one or more diseases, including a remedial measure for the one or more diseases.

Claims20

Dependent claims

A computer-implemented method of determining a number of kernels from an image of a corn, comprising:

receiving, by a processor, a digital image that is in encoded in color or gray scale;
segmenting the image into foreground data associated with a corn comprising a group of kernels grown on an ear of the corn and background data, to create an updated image;
identifying, by the processor, clusters of one or more connected pixels in the foreground data;
performing thresholding on a size of each of the clusters, thereby classifying the foreground data into one or more single-kernel areas and separate one or more multi-kernel areas based on a size of each of the clusters without further segmenting any of the clusters,
each of the one or more single-kernel areas corresponding to a single kernel,
each of the one or more multi-kernel areas corresponding to multiple kernels;
determining a total number of kernels based on one or more sizes of the one or more single-kernel areas and one or more sizes of the one or more multi-kernel areas;
causing a display of the total number of kernels.

5 more elements

One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of a method of determining a number of kernels from an image of a corn, the method comprising:

receiving a digital image that is in encoded in color or gray scale;
segmenting the image into foreground data associated with a corn comprising a group of kernels grown on an ear of the corn and background data, to create an updated image;
identifying clusters of one or more connected pixels in the foreground data;
performing thresholding on a size of each of the clusters, thereby classifying the foreground data into one or more single-kernel areas and separate one or more multi-kernel areas based on a size of each of the clusters without further segmenting any of the clusters,
each of the one or more single-kernel areas corresponding to a single kernel,
each of the one or more multi-kernel areas corresponding to multiple kernels;
determining a total number of kernels based on one or more sizes of the one or more single-kernel areas and one or more sizes of the one or more multi-kernel areas;
causing a display of the total number of kernels.

5 more elements

Dependencies are inferred from the claim text.

Crop disease recognition and yield estimation

Life of this patent

Crop disease recognition and yield estimation

Life of this patent

Abstract

Claims20