Sensor-synchronized spectrally-structured-light imaging
First Claim
1. An apparatus comprising:
- an imaging apparatus for obtaining pixels sampled from a produce item in a scene, the pixels each comprising an N-dimensional spectral vector, where N is an integer greater or equal to four, and corresponding to a number of spectral values obtained per pixel, the spectral values obtained from capture of the pixels by an image sensor in response to pulsed illumination of the object by 4 or more different LED light sources;
a digital signal processing device in communication with the imaging apparatus for computing texture feature values of the pixels at plural spatial scales, sampled from different locations of the produce item;
a classifier for classifying the produce item based on the N-dimensional spectral vector and texture feature values of the pixels at plural spatial scales to identify a variety of the produce item in the scene, wherein the classifier is trained on N-dimensional spectral vector and texture feature values of varieties of each of different produce items to discriminate between the varieties of each of the different produce items,the classifier configured to identify the variety of the produce item with a plural stage classifier, the plural stage classifier having a first stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector of the produce item for each of plural categories of produce, and a second stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector and texture feature values of the produce item for variety of produce within each of the plural categories; and
a display device configured to display identifying information of the variety of the produce item.
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Accused Products
Abstract
An image capture device, such as a smartphone or point of sale scanner, is adapted for use as an imaging spectrometer, by synchronized pulsing of different LED light sources as different image frames are captured by the image sensor. A particular implementation employs the CIE color matching functions, and/or their orthogonally transformed functions, to enable direct chromaticity capture. These and various other configurations of spectral capture devices are employed to capture spectral images comprised of spectral vectors having multi-dimensions per pixel. These spectral images are processed for use in object identification, classification, and a variety of other applications. Particular applications include produce (e.g., fruit or vegetable) identification. A great variety of other features and arrangements are also detailed.
96 Citations
16 Claims
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1. An apparatus comprising:
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an imaging apparatus for obtaining pixels sampled from a produce item in a scene, the pixels each comprising an N-dimensional spectral vector, where N is an integer greater or equal to four, and corresponding to a number of spectral values obtained per pixel, the spectral values obtained from capture of the pixels by an image sensor in response to pulsed illumination of the object by 4 or more different LED light sources; a digital signal processing device in communication with the imaging apparatus for computing texture feature values of the pixels at plural spatial scales, sampled from different locations of the produce item; a classifier for classifying the produce item based on the N-dimensional spectral vector and texture feature values of the pixels at plural spatial scales to identify a variety of the produce item in the scene, wherein the classifier is trained on N-dimensional spectral vector and texture feature values of varieties of each of different produce items to discriminate between the varieties of each of the different produce items, the classifier configured to identify the variety of the produce item with a plural stage classifier, the plural stage classifier having a first stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector of the produce item for each of plural categories of produce, and a second stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector and texture feature values of the produce item for variety of produce within each of the plural categories; and a display device configured to display identifying information of the variety of the produce item. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method of recognizing a produce item comprising:
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obtaining pixels sampled from a produce item in a scene, the pixels each comprising an N-dimensional spectral vector, the pixels being sampled under different illumination to obtain the N-dimensional spectral vector, comprising N different spectral samples per pixel, where N is an integer greater or equal to four, and corresponding to a number of spectral values obtained per pixel, the spectral values obtained from capture of the pixels by an image sensor in response to pulsed illumination of the object by 4 or more different LED light sources; computing texture feature values of the pixels at plural spatial scales, sampled from different locations of the produce item in the scene; with a trained classifier, classifying the produce item based on the N-dimensional spectral vector and the texture feature values of the pixels at plural spatial scales, wherein the classifier is trained on N-dimensional spectral vector and texture feature values of varieties of each of different produce items to discriminate between the varieties of each of the different produce items, the trained classifier configured to identify the variety of the produce item with a plural stage classifier, the plural stage classifier having a first stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector of the produce item for each of plural categories of produce, and a second stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector and texture feature values of the produce item for variety of produce within each of the plural categories; and displaying identifying information of the variety of the produce item. - View Dependent Claims (9, 10, 11)
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12. A non-transitory processor-readable medium comprising instructions that, when executed by a processor, cause the processor to:
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determine aggregate spectral values for a spectral image of a produce item, the spectral image comprising a two-dimensional array of pixels, with each pixel having a N-dimensional vector of spectral values captured of an object, where N is at least 4 and corresponds to different spectral bands obtained from capture of the pixels by an image sensor in response to pulsed illumination of the object by 4 or more different LED light sources, the aggregate spectral values being derived from a distribution of spectral values within each spectral band; determine aggregate texture feature values for the spectral image; and with a trained classifier, identify the variety of the produce item by submitting the aggregate spectral values and aggregate texture feature values to the trained classifier, wherein the trained classifier is trained on N-dimensional spectral vector and texture feature values of varieties of each of different produce items to discriminate between the varieties of each of the different produce items; the instructions further configured to cause the processor to identify the variety of the produce item with a plural stage classifier, the plural stage classifier having a first stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector of the produce item for each of plural categories of produce, and a second stage classifier comprising one-versus-one classifiers to discriminate the N-dimensional spectral vector and texture feature values of the produce item for variety of produce within each of the plural categories. - View Dependent Claims (13, 14, 15, 16)
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Specification