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Patent US0180211121
Inventor

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Average Length Specification


1 Independent Claims

  • Claim 2. The method of claim 1, further comprising formulating the RGB frame from RGB images fused from a plurality of cameras.
  • Claim 3. The method of claim 1, wherein filtering the "A" channel of the LAB frame comprises filtering the "A" channel of the LAB frame with a plurality of different size thresholds.
  • Claim 4. The method of claim 1, wherein extracting at least one contour comprises: identifying a plurality of contours from the at least one thresholded LAB imageand filtering the at least one contour from the plurality of contours, the at least one contour having shape and size more likely to correspond to a vehicle relative to other contours in the plurality of contours.
  • Claim 5. The method of claim 1, further comprising identifying at least one region of interest in the at least one thresholded LAB image, including for each of the at least one contours, cropping out a region of interest from the at least one thresholded LAB image that includes the contour.
  • Claim 7. The method of claim 1, further comprisingreceiving an RGB image from a camera at the vehicle, the RGB image captured when light intensity within environment around the vehicle was below a specified thresholdand extracting the RGB frame from the RGB image.
  • Claim 8. The method of claim 1, wherein converting an RGB frame to an LAB frame comprises converting an RGB frame that was captured at night by a camera at the vehicle.
  • Claim 9. The method of claim 1, wherein classifying, by a neural network, the at least one contour as another vehicle within the environment of the vehicle comprises sending the at least one contour along with range data from a LIDAR sensor to the neural network.
  • Claim 10. A vehicle, the vehicle comprising: one or more processorssystem memory coupled to one or more processors, the system memory storing instructions that are executable by the one or more processorsone or more cameras for capturing images of an environment around the vehicle the vehiclea neural network for determining if contours detected in the environment around the vehicle are other vehiclesand the one or more processors executing the instructions stored in the system memory to detect another vehicle in a low light environment around the vehicle, including the following: receive a Red, Green, Blue (RGB) image captured by the one or more cameras, the Red, Green, Blue (RGB) image of the low light environment around the vehicleconvert the Red, Green, Blue (RGB) image to an LAB color space imagefilter an "A" channel of the LAB image by one or more threshold values to obtain at least one thresholded LAB imageextract a contour from the at least one thresholded LAB image based on the size and shape of the contourand classify the contour as another vehicle within the low light environment around the vehicle based on an affinity to a vehicle classification determined by the neural network.
  • Claim 17. A method for use at a vehicle, the method for detecting another vehicle in a low light environment around the vehicle, the method comprising: receiving a Red, Green, Blue (RGB) image captured by one or more cameras at the vehicle, the Red, Green, Blue (RGB) image of the low light environment around the vehicleconverting the Red, Green, Blue (RGB) image to an LAB color space imagefiltering an "A" channel of the LAB image by at least one threshold value to obtain at least one thresholded LAB imageextracting a contour from the thresholded LAB image based on the size and shape of the contourand classifying the contour as another vehicle within the low light environment around the vehicle based on an affinity to a vehicle classification determined by a neural network.


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