Abstract: A method for processing a video stream of images captured by a color camera and used by a computer on board a motor vehicle to detect a priority vehicle, the method including: acquiring an image sequence; for each image of the image sequence: performing thresholding-based colorimetric segmentation, making it possible to detect colored luminous zones; tracking each segmented luminous zone; performing colorimetric classification of each segmented luminous zone; performing frequency analysis of each segmented luminous zone, making it possible to determine a flashing nature of the zone; computing an overall confidence index for each image of the image sequence, making it possible to declare a luminous zone as being a flashing light.

Abstract: A method for detecting false positives relating to a traffic light based on a video stream of images captured by a camera on board a motor vehicle, the traffic light being configured so as to switch between a plurality of states, each state being characterized by at least one colored zone representative of a signal. The method includes filtering the images, using a predetermined list of filtering criteria relating to the states of the traffic light, based on a predetermined history of the color of the pixels of the colored zone representing a luminous object detected in the video stream of images so as to detect false positives.

Abstract: A method for detecting false positives relating to a traffic light based on a video stream of images captured by a camera on board a motor vehicle, the traffic light being configured so as to switch between a plurality of states, each state being characterized by at least one colored zone representative of a signal. The method includes filtering the images, using a predetermined list of filtering criteria relating to the states of the traffic light, based on a predetermined history of the color of the pixels of the colored zone representing a luminous object detected in the video stream of images so as to detect false positives.

Abstract: To improve the performance for determining obstruction of a stereoscopic system using two cameras or more, a hybrid of local and semi-global methods is provided. For each stereoscopic image formed from simultaneous left and right images, a breakdown of each left and right image into corresponding sectors is applied. Obstruction level is determined by a disparity map by sector, based on left or right images, and in which a disparity is assigned to each pixel corresponding to the best matching score. A determination of density by sector of the disparity map is carried out by reference to a fraction of pixels with a disparity considered to be valid. A state of obstruction of at least one camera is determined based on a weighted average of the probabilities of obscuring of the sectors of the disparity map obtained by comparison between the density of the sectors and a predefined density level.

Abstract: To improve the performance for determining obstruction of a stereoscopic system using two cameras or more, a hybrid of local and semi-global methods is provided. For each stereoscopic image formed from simultaneous left and right images, a breakdown of each left and right image into corresponding sectors is applied. Obstruction level is determined by a disparity map by sector, based on left or right images, and in which a disparity is assigned to each pixel corresponding to the best matching score. A determination of density by sector of the disparity map is carried out by reference to a fraction of pixels with a disparity considered to be valid. A state of obstruction of at least one camera is determined based on a weighted average of the probabilities of obscuring of the sectors of the disparity map obtained by comparison between the density of the sectors and a predefined density level.