Three-dimensional measurement is performed by projecting patterned light having a hybrid pattern Ph onto a measurement target. The hybrid pattern Ph is a pattern in which a random pattern Pr is superimposed on a structured light pattern Ps, and is arranged in pattern such that the random pattern Pr and the structured light pattern Ps do not interfere mutually.

An imaging device comprises a hybrid optical sensor array including a first and second set of pixels that comprise different numbers of pixels. The first set of pixels is sensitive to infrared light, while the second set of pixels comprises three subsets of pixels sensitive to RGB light. A first set of data for a scene is captured by the first set of pixels and a second set of data for the scene is captured by a second set of pixels. The first and second sets of data are jointly demosaiced, such that the higher resolution data set is utilized to increase the resolution of a lower resolution data set. This allows for high-resolution infrared and RGB images to be produced for a scene without perspective or timing discrepancies inherent in multi-camera machine vision systems.

Disclosed herein is a method for acquiring a three-dimensional (3D) image including: acquiring a 3D primary image of an object from two-dimensional (2D) primary image data acquired by first and second cameras when a predetermined pattern is projected on the object by a projector and a 2D primary image of the pattern-projected object is acquired by the first and second cameras, and then converting it into a 2D re-viewpoint image; correcting a missing area in the 2D re-viewpoint image corresponding to the 3D data missing area for compensating for a 3D data missing area caused by a curvature of the object and the points of view of the first and second cameras; and generating a corrected 3D image by referring to the 2D primary image data acquired by the first or second camera and the corrected 2D re-viewpoint image information.

The subject disclosure is directed towards color correcting for infrared (IR) components that are detected in the R, G, B parts of a sensor photosite. A calibration process determines true R, G, B based upon obtaining or estimating IR components in each photosite, such as by filtering techniques and/or using different IR lighting conditions. A set of tables or curves obtained via offline calibration model the correction data needed for online correction of an image.

The present invention provides a multi-line array laser three-dimensional scanning system and a multi-line array laser three-dimensional scanning method, the system performs precise synchronization and logic control of the multi-line array laser three-dimensional scanning system by a programmable gate array FPGA; employs a line laser array as the projection pattern light source, sends trigger signals to a stereoscopic image sensor, a inertial sensor and a line laser array by FPGA; wherein a upper computer receives image pairs taken by the stereoscopic image sensor, and codes, decodes as well as performs a three-dimensional reconstruction for the laser line array patterns in the image pairs, performs a three-dimensional reconstruction for the feature points on the surface of the measured object, and matches and aligns the three-dimensional feature points at different times; the system predicts and corrects the matching calculation by employing a hybrid sensing technology, which registers and stitches the time domain laser three-dimensional scanning data, meanwhile evaluates the error level in real time and feeds it back to an error feedback controller to obtain an adjustment instruction. Thereby the system performs a laser three-dimensional scanning with low cost, high efficiency, high reliability and high accuracy.

A triangulation scanner includes a projector, a camera, and a processor, the projector projecting a first pattern of light on a first point during first intervals and a no light during second intervals, the camera including an optical detector, a first accumulator, and a second accumulator, the optical detector receiving reflected light from the first point, the first and second accumulators summing signals from the optical detector during the first and second intervals, respectively, the processor determining 3D coordinates of the first point based at least in part on the first pattern, the summed signals from the first and second accumulators, and a speed of light in air.

Various embodiments may include a measuring apparatus for the 3D measurement of an object having a recess by means of triangulation comprising: a single capture device; and an optical device placed between the single capture device and the object. The optical device generates a plurality of separate optical paths which divide a single original field of view of the capture device into a plurality of sub-fields of view. The single capture device captures the sub-fields of view separately.

An image processing apparatus includes: an acquisition unit that acquires a plurality of first images that correspond to a plurality of spatial frequencies on a one-to-one basis; and a generation unit that generates a second image by synthesizing the first images acquired by the acquisition unit.

A measuring system can three-dimensionally reconstruct surface geometry of an object by, from a first pose with a sensor, generating a first three-dimensional representation of a first portion of the object, and with a first camera, generating a first image covering at least part of the first portion, and from a second pose with the sensor, generating a second three-dimensional representation of a second portion of the object, and with the first camera, generating a second image covering at least part of the second portion. A stationary first projector can be arranged externally configured for projecting a texture onto both first and second portions of the object. A stitching computer can be configured for generating a unitary three-dimensional representation of both the first and second portions of the object from the first and second three-dimensional representations based on the first and second images.

Described are mechanisms for depth sensor optimization based on detected distances. The mechanisms may comprise a distance measurement module, which may be operable to measure a physical distance between a 3D camera sensor and a person or object in view of the 3D camera. The mechanisms may also comprise a sensor mode selector module, which may be operable to select a best camera sensor configuration based on a measured distance from a distance-measurement module.