The present invention extends to methods, systems, and computer program products for detecting vehicles in low light conditions. Cameras are used to obtain RGB images of the environment around a vehicle. RGB images are converted to LAB images. The “A” channel is filtered to extract contours from LAB images. The contours are filtered based on their shapes/sizes to reduce false positives from contours unlikely to correspond to vehicles. A neural network classifies an object as a vehicle or non-vehicle based the contours. Accordingly, aspects provide reliable autonomous driving with lower cost sensors and improved aesthetics. Vehicles can be detected at night as well as in other low light conditions using their head lights and tail lights, enabling autonomous vehicles to better detect other vehicles in their environment. Vehicle detections can be facilitated using a combination of virtual data, deep learning, and computer vision.
Claim CLM-00001. 1. A method for detecting another vehicle in a vehicle environment, comprising:
converting an RGB frame to an LAB frame; filtering an “A” channel of the LAB frame by at least one threshold value to obtain at least one thresholded LAB image; extracting at least one contour from the at least one thresholded LAB image; and classifying, by a neural network, the at least one contour as another vehicle within the environment of the vehicle.
Claim CLM-00010. 10. A vehicle, the vehicle comprising:
one or more processors; system memory coupled to one or more processors, the system memory storing instructions that are executable by the one or more processors; one or more cameras for capturing images of an environment around the vehicle the vehicle; a neural network for determining if contours detected in the environment around the vehicle are other vehicles; and 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 vehicle;convert the Red, Green, Blue (RGB) image to an LAB color space image;filter an “A” channel of the LAB image by one or more threshold values to obtain at least one thresholded LAB image;extract a contour from the at least one thresholded LAB image based on the size and shape of the contour; andclassify 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 CLM-00017. 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 vehicle; converting the Red, Green, Blue (RGB) image to an LAB color space image; filtering an “A” channel of the LAB image by at least one threshold value to obtain at least one thresholded LAB image; extracting a contour from the thresholded LAB image based on the size and shape of the contour; and 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.
