Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of a food object by an imaging device, the hyperspectral image of the food object comprising a three-dimensional set of images of the food object, each image in the set of images representing the food object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the food object, select a region of interest in the hyperspectral image, the region of interest comprising a subset of at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the food object and determine that the hyperspectral image indicates a foreign object.

Abstract: A system includes a memory and at least one processor to acquire a hyperspectral image of an object by an imaging device, the hyperspectral image of the object comprising a three-dimensional set of images of the object, each image in the set of images representing the object in a wavelength range of the electromagnetic spectrum, normalize the hyperspectral image of the object, select a region of interest in the hyperspectral image, the region of interest comprising at least one image in the set of images, extract spectral features from the region of interest in the hyperspectral image, and compare the spectral features from the region of interest with a plurality of images in a training set to determine particular characteristics of the object.