Application US20180211121

Detecting Vehicles In Low Light Conditions

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.