8 results about "Optical triangulation" patented technology

In a 3D imaging system based on optical triangulation, this provides indicators such as measured and / or estimated values ​​of intensity peak width in image data from an image sensor. [Solution] An arrangement and method performed by one or more devices for providing information indicating the intensity peak width of an intensity peak along a pixel line of a pixel containing an intensity peak. The intensity peak is formed from such reflected light sensed by an image sensor. A first value is calculated, including the magnitude of a lower-order Discrete Fourier Transform (DFT) coefficient for the pixel intensity value of the pixel along the pixel line containing the intensity peak (601). A second value is calculated, including the magnitude of another higher-order DFT coefficient for the pixel intensity value of the pixel along the pixel line containing the intensity peak (602). Information indicating the intensity peak width is provided based on the first and second values ​​(603).

To provide methods and arrangements for obtaining multispectral 2D image data and associating the data with 3D image data from light triangulation.SOLUTION: A method comprises: obtaining 601 3D image data as first sensor positions (SP1s) of first images (IM1s) corresponding to locations of intensity peaks of a reflected first light beam from an object as part of the light triangulation; obtaining 602 two or more second images (IM2s) by means of multispectral two or more second light beams; selecting 603 respective second sensor positions (SP2s) in the respective IM2s for the respective SP1s; and associating 604 intensity values of the selected SP2s with the SP1s; so that multispectral 2D data corresponding to the intensity values in the SP2s from the reflected multispectral second light beams become associated with the 3D data corresponding to the SP1s.SELECTED DRAWING: Figure 6

An apparatus and a method performed by one or more devices (205; 231; 331; 1000) for providing information indicating the width (371; 471; 571) of the intensity peak (363; 463; 563) of an intensity peak (366; 466; 566) along a pixel line (352-m) including an intensity peak (363; 463; 563). The pixels correspond to pixel elements of an image sensing region (351) of an image sensor (231; 331). The intensity peak (363; 463; 563) is formed by reflected light sensed by the image sensor (231; 331). Calculate (601) a first value, which includes the magnitude of a low-order Discrete Fourier Transform (DFT) coefficient (473; 573) relating to the pixel intensity values ​​of pixels (366; 466; 566) along a pixel line (352-m) including intensity peaks (363; 463; 563). Calculate (602) a second value, which includes the magnitude of another high-order DFT coefficient (473; 573) relating to the pixel intensity values ​​of pixels (366; 466; 566) along a pixel line (352-m) including intensity peaks (363; 463; 563). Based on the first and second values, provide (603) the information indicating the width of the intensity peaks (371; 471; 571).

One aspect of this disclosure relates to a method and arrangement for determining information about the location of an intensity peak in a spatial-temporal volume of an image frame. The method discloses the determination of information about the location of an intensity peak in a spatial-temporal volume formed by an image frame generated by an image sensor by sensing light reflected from a measured object as part of optical triangulation. The spatial-temporal volume is also associated with a spatial-temporal trajectory relating to how feature points of the measured object are mapped to locations within the spatial-temporal volume. A first hypothetical intensity peak location HIPP1 is obtained within the spatial-temporal volume. A first spatial-temporal analysis location STAP1 is calculated based on a spatial-temporal analysis performed locally around HIPP1 and along the first spatial-temporal trajectory associated with HIPP1. The information about the intensity peak location is determined based on HIPP1 and STAP1.

The application discloses a kind of based on 3D vision's packaging chip substrate face warping detection method and system, method includes: the real three-dimensional view of chip is obtained by the structured light projection technology in optical triangulation;Based on template matching algorithm, complete chip area is extracted in depth map;Depth map is converted into three-dimensional point cloud data using inverse projection conversion;The point cloud data obtained is filtered, and noise point not belonging to substrate surface is removed;Multiple regions of interest are set on substrate surface, and ROI meeting conditions are screened and retained;RANSAC random sampling consistency algorithm is used to plane fitting reserved ROI to generate reference surface;The maximum and minimum perpendicular distance of each point on substrate surface to reference surface is calculated, and combined with set threshold value, warping is quantitatively judged, to determine whether chip exists warping deformation.The application can effectively extract the warping parameter of single chip, realize the automatic determination of chip warping state.

The utility model provides a boiler thermal expansion monitoring device which comprises a monitoring mechanism. The monitoring mechanism comprises a protective cover, a light output window and a light input window are arranged on the face, facing the to-be-monitored object, of the protective cover, and a first collimating mirror and a second collimating mirror are arranged on the inner wall of the light output window and the inner wall of the light output window respectively. During use, the protective cover is arranged on the side face of the boiler, the light output window and the light input window are arranged on the protective cover, laser is emitted to the light output window through the laser emitting head to the outer surface of the boiler, and the laser is reflected on the outer surface of the boiler, passes through the light input window and then is emitted to the linear CCD matrix; according to an optical triangulation method, the signal processor calculates the expansion coefficient of the boiler according to different positions of reflected light received by the linear CCD matrix and transmits data to the outside in real time, and the real-time monitoring effect can be achieved.

The invention discloses a packaging chip substrate surface warping degree detection method and system based on 3D vision. The method comprises the following steps: obtaining a real three-dimensional view of a chip through a structured light projection technology in optical triangulation; based on a template matching algorithm, extracting a complete chip area in the depth map; converting the depth map into three-dimensional point cloud data by adopting inverse projection transformation; filtering the obtained point cloud data to remove noise points which do not belong to the substrate surface; setting a plurality of regions of interest on the surface of the substrate, and screening and reserving ROIs (Region of Interest) meeting conditions; performing plane fitting on the reserved ROI by adopting an RANSAC random sampling consensus algorithm to generate a reference plane; and calculating the maximum vertical distance and the minimum vertical distance from each point on the substrate surface to the reference surface, and carrying out quantitative judgment on the warping degree in combination with a set threshold value so as to determine whether the chip has warping deformation or not. According to the method, the warping degree parameter of the single chip can be effectively extracted, and the automatic judgment of the warping state of the chip is realized.

A method relating to providing pixel values ​​of image sensor pixels of a second ROI based on a first ROI, and an imaging system for 3D imaging based on optical triangulation including an image sensor. [Solution] A first ROI is used by the image sensor to provide a first pixel value of the image sensor pixels of the first ROI resulting from a first exposure. A second ROI is determined according to a predetermined relationship that the second ROI has with respect to the first ROI (702). A second exposure (703) causes at least the image sensor pixels of the second ROI to acquire a second pixel value. The second ROI is used to provide a second pixel value of the image sensor pixels of the second ROI for further processing by the image sensor (704).