Abstract: The present invention relates to a method for calibrating an agricultural spraying machine comprising a plurality of spray nozzles arranged on the spray boom, at least one optical sensor and a control system, each optical sensor of said at least one optical sensor having a field of view comprising sectors, each of the sectors being associated with a spray nozzle, the control system being configured to control the plurality of spray nozzles as a function of images acquired by the optical sensors, the calibration method comprising, for an optical sensor, an automatic association implemented by the control system of each sector of the field of view of the corresponding optical sensor with a spray nozzle of the plurality of spray nozzles.

Abstract: A blade pitch measuring device of an un-ducted fan of a turbomachine, the fan including a hub, at least one platform rotatable with respect to the hub and at least one blade mounted on the platform, the device includes at least one first visual marker attached to the platform, at least one second visual marker attached to the hub, the first and the second visual marker forming a pattern which evolves depending on the pitch of the blade, and at least one optical acquisition device, the optical acquisition device being configured to capture an image of the pattern so as to deduce from it the pitch of the blade.

Abstract: A blade pitch measuring device of an un-ducted fan of a turbomachine, the fan including a hub, at least one platform rotatable with respect to the hub and at least one blade mounted on the platform, the device includes at least one first visual marker attached to the platform, at least one second visual marker attached to the hub, the first and the second visual marker forming a pattern which evolves depending on the pitch of the blade, and at least one optical acquisition device, the optical acquisition device being configured to capture an image of the pattern so as to deduce from it the pitch of the blade.

Abstract: A method for estimating the image depth map of a scene, includes the following steps: providing (E1) an image, the focus of which depends on the depth and wavelength of the considered object points of the scene, using a longitudinal chromatic optical system; determining (E2) a set of spectral images from the image provided by the longitudinal chromatic optical system; deconvoluting (E3) the spectral images to provide estimated spectral images with field depth extension; and analyzing (E4) a cost criterion depending on the estimated spectral images with field depth extension to provide an estimated depth map.

Abstract: A method for estimating the image depth map of a scene, includes the following steps: providing (E1) an image, the focus of which depends on the depth and wavelength of the considered object points of the scene, using a longitudinal chromatic optical system; determining (E2) a set of spectral images from the image provided by the longitudinal chromatic optical system; deconvoluting (E3) the spectral images to provide estimated spectral images with field depth extension; and analyzing (E4) a cost criterion depending on the estimated spectral images with field depth extension to provide an estimated depth map.

Abstract: A method for calculating a depth map from an original matrix image, comprising the steps of: calculating a first matrix image corresponding to the original matrix image with a low resolution and in which the depth of field is similar to that of the original matrix image, calculating a second matrix image corresponding to the original matrix image with a low resolution, comprising a number of pixels similar to that of the first matrix image and in which the depth of field is greater than that of the original matrix image, implementing a DFD type three-dimensional reconstruction algorithm from the first and the second matrix images, outputting the depth map.

Abstract: A method for calculating a depth map from an original matrix image, comprising the steps of: calculating a first matrix image corresponding to the original matrix image with a low resolution and in which the depth of field is similar to that of the original matrix image, calculating a second matrix image corresponding to the original matrix image with a low resolution, comprising a number of pixels similar to that of the first matrix image and in which the depth of field is greater than that of the original matrix image, implementing a DFD type three-dimensional reconstruction algorithm from the first and the second matrix images, outputting the depth map.