A method includes steps of: capturing an image of a container; recognizing at least one object in the container based on the image; determining at least one first coordinate set corresponding to the at least one object; determining at least one second coordinate set that corresponds to target one (s) of the at least one first coordinate set and that relates to a fixed picking device of a robotic arm; adjusting position(s) of unfixed picking device(s) of the robotic arm if necessary; controlling the robotic arm to pick up one (s) of the at least one object that correspond(s) to the at least one second coordinate set with the fixed picking device and/or at least one unfixed picking device.

A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.

A farming machine moves through a field and includes an image sensor that captures an image of a plant in the field. A control system accesses the captured image and applies the image to a machine learned plant identification model. The plant identification model identifies pixels representing the plant and categorizes the plant into a plant group (e.g., plant species). The identified pixels are labeled as the plant group and a location of the pixels is determined. The control system actuates a treatment mechanism based on the identified plant group and location. Additionally, the images from the image sensor and the plant identification model may be used to generate a plant identification map. The plant identification map is a map of the field that indicates the locations of the plant groups identified by the plant identification model.

A method for automatically reconstituting the architecture, along a reinforcing axis, of the reinforcement of a composite material, includes acquiring images of the reinforcement of the composite material, each image being acquired along a section plane perpendicular to the reinforcing axis; for each image acquired, detecting, using a neural network, barycentre and/or the circumference of each section of the reinforcing thread; for at least one acquired reference image, assigning a tag corresponding to a reinforcing thread, to each detected barycentre or circumference; for each other acquired image, assigning, to each detected barycentre and/or each detected circumference, the tag of the corresponding barycentre in the acquired reference image; reconstituting the architecture of each reinforcing thread from each detected barycentre and/or circumference having the tag of the reinforcing thread and the position on the reinforcing axis associated with the acquired image on which the barycentre and/or the circumference has been detected.

A method for automatically reconstituting the architecture, along a reinforcing axis, of the reinforcement of a composite material, includes acquiring images of the reinforcement of the composite material, each image being acquired along a section plane perpendicular to the reinforcing axis; for each image acquired, detecting, using a neural network, barycentre and/or the circumference of each section of the reinforcing thread; for at least one acquired reference image, assigning a tag corresponding to a reinforcing thread, to each detected barycentre or circumference; for each other acquired image, assigning, to each detected barycentre and/or each detected circumference, the tag of the corresponding barycentre in the acquired reference image; reconstituting the architecture of each reinforcing thread from each detected barycentre and/or circumference having the tag of the reinforcing thread and the position on the reinforcing axis associated with the acquired image on which the barycentre and/or the circumference has been detected.

An image processing method performed by a processor and including detecting positions of plural vortex veins in a fundus image of an examined eye, and computing a center of distribution of the plural detected vortex vein positions.

This application disclosures a method and system for detecting a centerline of a vessel. The method may include obtaining image data, wherein the image data may include vessel data; selecting two endpoints of the vessel based on the vessel data; transforming the image data to generate a transformed image based on at least one image transformation function; and determining a path of the centerline of the vessel connecting the first endpoint of the vessel and the second endpoint of the vessel to obtain the centerline of the vessel based on the transformed image. The two endpoints of the vessel may include a first endpoint of the vessel and a second endpoint of the vessel.

This application disclosures a method and system for detecting a centerline of a vessel. The method may include obtaining image data, wherein the image data may include vessel data; selecting two endpoints of the vessel based on the vessel data; transforming the image data to generate a transformed image based on at least one image transformation function; and determining a path of the centerline of the vessel connecting the first endpoint of the vessel and the second endpoint of the vessel to obtain the centerline of the vessel based on the transformed image. The two endpoints of the vessel may include a first endpoint of the vessel and a second endpoint of the vessel.

A target reflector search device. This device comprises an emitting unit for emitting an emission fan, a motorized device for moving the emission fan over a spatial region, and a receiving unit for reflected portions of the emission fan within a fan-shaped acquisition region, and a locating unit for determining a location of the reflection. An optoelectronic detector of the receiving unit is formed as a position-resolving optoelectronic detector having a linear arrangement of a plurality of pixels, each formed as an SPAD array, and the receiving unit comprises an optical system having an imaging fixed-focus optical unit, wherein the optical system and the optoelectronic detector are arranged and configured in such a way that portions of the optical radiation reflected from a point in the acquisition region are expanded on the sensitivity surface of the optoelectronic detector in such a way that blurry imaging takes place.

A target reflector search device. This device comprises an emitting unit for emitting an emission fan, a motorized device for moving the emission fan over a spatial region, and a receiving unit for reflected portions of the emission fan within a fan-shaped acquisition region, and a locating unit for determining a location of the reflection. An optoelectronic detector of the receiving unit is formed as a position-resolving optoelectronic detector having a linear arrangement of a plurality of pixels, each formed as an SPAD array, and the receiving unit comprises an optical system having an imaging fixed-focus optical unit, wherein the optical system and the optoelectronic detector are arranged and configured in such a way that portions of the optical radiation reflected from a point in the acquisition region are expanded on the sensitivity surface of the optoelectronic detector in such a way that blurry imaging takes place.