Methods and arrangements for configuring industrial inspection systems
First Claim
1. A camera configuration method comprising the acts:
- capturing a first image of a subject with a camera, the camera employing a first combination of values for first and second imaging parameters, at least one of said first and second imaging parameters being selected from the group consisting of;
exposure interval, camera gain, illumination intensity, and flash illumination interval;
computing a probability distribution measure, said probability distribution measure comprising a difference, or similarity, between a probability distribution of pixel values in the first image, and a second probability distribution;
capturing additional images of the subject with the camera, employing other combinations of values for said first and second imaging parameters, and, for each additional image, computing said probability distribution measure comprising a difference or similarity between a probability distribution of pixel values in the further image, and the second probability distribution;
identifying which combination of values for the first and second imaging parameters yields a most extreme value of said probability distribution measure; and
setting the camera to use said combination of values for the first and second imaging parameters in capturing subsequent images;
wherein said act of identifying a combination of values for the first and second imaging parameters yielding a most extreme value of said probability distribution measure has the practical effect of establishing an optimal set of imaging parameters to best allow machine detection of subtle features from imagery.
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Abstract
In computer vision systems that need to decode machine-readable indicia from captured imagery, it is critical to select imaging parameters (e.g., exposure interval, exposure aperture, camera gain, intensity and duration of supplemental illumination) that best allow detection of subtle features from imagery. In illustrative embodiments, a Shannon entropy metric or a KL divergence metric is used to guide selection of an optimal set of imaging parameters. In accordance with other aspects of the technology, different strategies identify which spatial locations within captured imagery should be successively examined for machine readable indicia, in order to have a greatest likelihood of success, within a smallest interval of time. A great variety of other features and arrangements are also detailed.
74 Citations
29 Claims
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1. A camera configuration method comprising the acts:
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capturing a first image of a subject with a camera, the camera employing a first combination of values for first and second imaging parameters, at least one of said first and second imaging parameters being selected from the group consisting of;
exposure interval, camera gain, illumination intensity, and flash illumination interval;computing a probability distribution measure, said probability distribution measure comprising a difference, or similarity, between a probability distribution of pixel values in the first image, and a second probability distribution; capturing additional images of the subject with the camera, employing other combinations of values for said first and second imaging parameters, and, for each additional image, computing said probability distribution measure comprising a difference or similarity between a probability distribution of pixel values in the further image, and the second probability distribution; identifying which combination of values for the first and second imaging parameters yields a most extreme value of said probability distribution measure; and setting the camera to use said combination of values for the first and second imaging parameters in capturing subsequent images; wherein said act of identifying a combination of values for the first and second imaging parameters yielding a most extreme value of said probability distribution measure has the practical effect of establishing an optimal set of imaging parameters to best allow machine detection of subtle features from imagery. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 24, 25, 26, 27, 28, 29)
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13. An inspection system for a production line that packages food or that applies labels to food containers, comprising:
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a camera directed towards the production line to capture imagery of objects conveyed by the production line, the camera employing first and second imaging parameters, at least one of said first and second imaging parameters being selected from the group consisting of;
exposure interval, camera gain, illumination intensity, and flash illumination interval; andmeans for determining optimal values of said first and second imaging parameters, to best allow decoding of payload data from 2D indicia on said objects depicted in imagery captured by said camera, wherein said means includes; software executing on a processor that causes the system to repeatedly collect image data from one or more objects, using different combinations of values for the first and second imaging parameters; software executing on a processor that causes the system to determine, from the collected image data, for each different combination of values for the first and second imaging parameters, an entropy or divergence value; and software executing on a processor that causes the system identify which of said different combinations of values for the first and second imaging parameters yields a largest entropy value or a smallest divergence value; wherein the combination of values for the first and second imaging values thereby identified is determined to comprise said optimal values for said first and second imaging parameters. - View Dependent Claims (14)
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15. A method comprising the acts:
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capturing plural image frames depicting a subject with a camera in an environment, the camera capturing each image frame with a particular combination of values for first and second imaging parameters, at least one of said first and second imaging parameters being selected from the group consisting of;
exposure interval, camera gain, illumination intensity, and flash illumination interval, wherein different of said image frames are captured with different combinations of values for said first and second imaging parameters;analyzing the captured image frames to identify which of said combinations of imaging parameter values is optimum for capture of imagery by said camera in said environment, by computing entropy or divergence metrics from the captured image frames, and identifying an extrema of said computed metrics; and setting the camera to employ said identified combination of imaging parameter values in capturing an image of an object; wherein the method has the practical effect of establishing an optimal set of imaging parameters for capturing images with said camera in said environment. - View Dependent Claims (16, 17, 18, 19, 20, 21, 22, 23)
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Specification