There is provided a system for detecting an object crossing a plane at high resolution from long range, the system including a first transmitter projecting a light plane using a light comprising a light plane wavelength, the light plane defining a boundary, wherein the light plane wavelength is not visible to the human eye, a first receiver for detecting a reflection of light when an object crosses the light plane defining the boundary, the receiver configured to detect light in a range of the electromagnetic spectrum including the light plane wavelength, wherein the receiver includes an image sensor comprising a plurality of sensor pixels, and an image processing computer configured to receive an input from the receiver including a recorded frame captured by the receiver, wherein the image processing computer processes the recorded frame for review to identify a frame showing an object crossing the boundary.

A security document may include a laserizable first layer including a grayscale image formed by laserizing; a color pattern that is in alignment with the grayscale image; and a second layer arranged between the first layer and the pattern, such that the first layer is above the second layer, and the pattern is below the second layer. The second layer may be more opaque than the first layer, such that when observing the security document from the top, the grayscale image appears to be colored by the color pattern only when the bottom of the security document is being illuminated.

A processing system comprises a processor and a memory. The memory stores instructions executable by the processor to receive a polarimetric image from a polarimetric camera sensor, and to identify a road surface in the received image based on a vehicle location, an orientation of the camera sensor, and a vehicle pose. The memory stores instructions, upon identifying, in the polarimetric image, polarized light reflections from the identified road surface based on a polarization direction and a polarization degree determined from the polarimetric image, to remove the identified polarized light reflections from the polarimetric image, thereby generating an updated polarimetric image including generating a de-mosaicked imaged based on the identified polarized light reflections, wherein the identified polarized light reflections are ignored at de-mosaicking, and to identify a road feature including a lane marking based on the updated polarimetric image.

Structured light is projected onto an object, and an image of the object as illuminated by the projected structured light is captured. Reference object points are identified within the captured image, and the structured light projected onto the object is modified based on the identified reference object points. An additional image of the object as illuminated by the modified projected structured light is captured, and additional reference object points are identified within the captured additional image.

Structured light is projected onto an object, and an image of the object as illuminated by the projected structured light is captured. Reference object points are identified within the captured image, and the structured light projected onto the object is modified based on the identified reference object points. An additional image of the object as illuminated by the modified projected structured light is captured, and additional reference object points are identified within the captured additional image.

Disclosed is a method for recognizing a bitting code of a key. The method comprises: using a back light source and/or a lateral light source to collect an image of a key to be recognized; and recognizing, on the basis of the image, a bitting code of the key to be recognized. Further disclosed are an apparatus for recognizing a bitting code of a key, and a storage medium and an image collection device. The present disclosure can improve the efficiency of recognizing a bitting code of a key and reduce the wear of the key during a recognition process.

Disclosed is a method for recognizing a bitting code of a key. The method comprises: using a back light source and/or a lateral light source to collect an image of a key to be recognized; and recognizing, on the basis of the image, a bitting code of the key to be recognized. Further disclosed are an apparatus for recognizing a bitting code of a key, and a storage medium and an image collection device. The present disclosure can improve the efficiency of recognizing a bitting code of a key and reduce the wear of the key during a recognition process.

A projection system and a method for selecting an image capturing number for image blending are provided. Multiple projection devices are driven one-by-one to project a pattern; multiple image capturing devices are driven to capture the pattern projected by each projection device, so as to obtain multiple image capturing results corresponding to the image capturing devices. Finally, at least one of the image capturing devices is selected to serve as an image capturing source for image blending based on the image capturing results. An image capturing range is identified through projected patterns, and an effective range is calculated and then selected for use, which is used for calculations required for automatic blending, so as to avoid a problem of being unable to maintain blending and merging due to environmental influences or failure of the image capturing device when performing image recognition and calculation required for automatic blending and merging.

A projection system and a method for selecting an image capturing number for image blending are provided. Multiple projection devices are driven one-by-one to project a pattern; multiple image capturing devices are driven to capture the pattern projected by each projection device, so as to obtain multiple image capturing results corresponding to the image capturing devices. Finally, at least one of the image capturing devices is selected to serve as an image capturing source for image blending based on the image capturing results. An image capturing range is identified through projected patterns, and an effective range is calculated and then selected for use, which is used for calculations required for automatic blending, so as to avoid a problem of being unable to maintain blending and merging due to environmental influences or failure of the image capturing device when performing image recognition and calculation required for automatic blending and merging.

A particle detection method detects presence and location of particles on a target using measured signals from a plurality of structured illumination patterns. The particle detection method uses measured signals obtained by illuminating the target with structured illumination patterns to detect particles. Specifically, the degree of variation in these measured signals in raw images is calculated to determine whether a particle is present on the target at a particular area of interest.