Abstract: A method for determining chlorophyll content of a plant comprises capturing a first image comprising light transmitted through a leaf of a plant; capturing a second image comprising light reflected from the leaf of the plant; estimating, from a plurality of pixels in the first image, a transmissive chlorophyll concentration value of the leaf; estimating a reflectance chlorophyll concentration value for the leaf from a plurality of pixels in the second image using bidirectional reflectance parameters for which a variance of the reflectance chlorophyll concentration value across the plurality of pixels in the second image is reduced; and determining an estimated chlorophyll concentration value for the plant based at least on the transmissive chlorophyll concentration value and the reflectance chlorophyll concentration value.

Abstract: Methods and apparatus are provided for determining moisture content of corn. In one example, a method includes processing a captured image of an ear of corn using a threshold value to create a segmented binary image comprising a first plurality of blobs, determining at least one characteristic of a plurality of corn kernels represented by the first plurality of blobs, and estimating a moisture value for the ear of corn based on the at least one characteristic of the plurality of corn kernels. In some embodiments, the method includes generating a luminance intensity profile across a region of the captured image containing at least one corn kernel in the plurality of corn kernels, computing a derivative of the luminance intensity profile; an determining, with reference to the derivative of the luminance intensity profile, a location of a boundary of the at least one corn kernel.

Abstract: Methods and apparatus are provided for identifying optimal threshold values to generate optimal binary images from a digital image. In one example, a method includes, for each of a plurality of candidate threshold values, processing an image using the candidate threshold value to create a first segmented image of a first plurality of blobs; for each of the plurality of candidate threshold values, calculating a threshold value evaluation metric as a count of qualifying blobs in the first plurality of blobs in the first segmented image, wherein the qualifying blobs have a fill factor exceeding a predefined fill factor and have an area within a predefined area range; identifying an optimal threshold value from the plurality of candidate threshold values for which the threshold value evaluation metric is maximized; and processing the image using the optimal threshold value to create a second segmented image of a second plurality of blobs.

Abstract: A method for generating a yield estimate for a crop of corn includes capturing a digital image of an ear of corn; processing the digital image of an ear of corn to determine a plurality of dimensions for each of a plurality of kernels on the ear of corn; estimating, from the plurality of dimensions, an average kernel volume for the ear of corn; determining, from the average kernel volume and an estimated kernel density, an average kernel weight for the ear of corn; and estimating, from the average kernel weight, a kernels-per-bushel for the ear of corn.

Abstract: A method for generating a yield estimate for a crop of corn includes capturing a digital image of an ear of corn; processing the digital image of an ear of corn to determine a plurality of dimensions for each of a plurality of kernels on the ear of corn; estimating, from the plurality of dimensions, an average kernel volume for the ear of corn; determining, from the average kernel volume and an estimated kernel density, an average kernel weight for the ear of corn; and estimating, from the average kernel weight, a kernels-per-bushel for the ear of corn.

Abstract: A method for determining chlorophyll content of a plant comprises capturing a first image comprising light transmitted through a leaf of a plant; capturing a second image comprising light reflected from the leaf of the plant; estimating, from a plurality of pixels in the first image, a transmissive chlorophyll concentration value of the leaf; estimating a reflectance chlorophyll concentration value for the leaf from a plurality of pixels in the second image using bidirectional reflectance parameters for which a variance of the reflectance chlorophyll concentration value across the plurality of pixels in the second image is reduced; and determining an estimated chlorophyll concentration value for the plant based at least on the transmissive chlorophyll concentration value and the reflectance chlorophyll concentration value.

Abstract: Methods and apparatus are provided for determining moisture content of corn. In one example, a method includes processing a captured image of an ear of corn using a threshold value to create a segmented binary image comprising a first plurality of blobs, determining at least one characteristic of a plurality of corn kernels represented by the first plurality of blobs, and estimating a moisture value for the ear of corn based on the at least one characteristic of the plurality of corn kernels. In some embodiments, the method includes generating a luminance intensity profile across a region of the captured image containing at least one corn kernel in the plurality of corn kernels, computing a derivative of the luminance intensity profile; an determining, with reference to the derivative of the luminance intensity profile, a location of a boundary of the at least one corn kernel.

Abstract: Methods and apparatus are provided for identifying optimal threshold values to generate optimal binary images from a digital image. In one example, a method includes, for each of a plurality of candidate threshold values, processing an image using the candidate threshold value to create a first segmented image of a first plurality of blobs; for each of the plurality of candidate threshold values, calculating a threshold value evaluation metric as a count of qualifying blobs in the first plurality of blobs in the first segmented image, wherein the qualifying blobs have a fill factor exceeding a predefined fill factor and have an area within a predefined area range; identifying an optimal threshold value from the plurality of candidate threshold values for which the threshold value evaluation metric is maximized; and processing the image using the optimal threshold value to create a second segmented image of a second plurality of blobs.