13 results about "Industrial imaging" patented technology

1. Name of the designed product: industrial camera. 2. Use of the designed product: the product is used for industrial imaging and is suitable for product quality inspection. 3. Design points of the designed product: in shape. 4. Picture or photo that best indicates the design points: perspective view 1.

Disclosed herein is a circularity-invariant method for accurately determining the perimeter of a particle in a digital image. Conventional pixel-based perimeter estimation methods overestimate curved boundaries due to rigid assignment of diagonal pixel distances (√2), leading to errors in circularity and derived shape parameters. The disclosed method segments the particle, identifies boundary pixels, classifies them as orthogonal or diagonal, and applies an adaptive corrective factor defined as 1 + (D / X × 0.414), where D is the number of diagonal pixels and X is the total boundary pixels. This adjustment mitigates systematic overestimation, ensuring accurate, rotation-invariant perimeter estimation. The method improves calculation of circularity, convexity and high sensitivity circularity (HSC). It is computationally efficient, resolution-independent, and suitable for integration into industrial imaging workflows across materials science, pharmaceuticals, and biomedical applications.

The application provides an industrial CT image coupling artifact multi-scale generative adversarial network correction method, and belongs to the field of digital image processing. The method aims at the problem that image degradation caused by the coupling of various artifacts in industrial CT imaging is difficult to correct effectively, and provides a multi-scale generative adversarial network correction method. The feature pyramid structure is used to help the network capture more comprehensive artifact feature information, and a multi-scale discriminator is used to build a generative adversarial network framework, so that the generated artifact-removed image is clearer and more real. The method has strong coupling artifact correction capability, and can better restore the detail information of the image, thereby ensuring the accuracy of the geometric size and contour edge of the part in the CT image.

1. Name of the designed product: industrial camera. 2. Use of the designed product: the product is used for industrial imaging and is suitable for product quality inspection. 3. Design points of the designed product: in shape. 4. Picture or photo that best indicates the design points: perspective view 1.

1. Name of the product in this design: Industrial Camera. 2. Purpose of this design: As an industrial camera, used for industrial imaging. 3. The key design features of this product are the combination of shape and pattern. 4. The picture or photo that best illustrates the key design points: Design 1 3D diagram 1. 5. Design 1 is designated as the basic design.

The invention relates to an automatic exposure method for internal imaging of an aluminum casting hole in an industrial quality inspection scene in the technical field of industrial imaging. The automatic exposure method comprises the following steps: determining the maximum exposure time corresponding to an image average gray value meeting a detection requirement; determining an exposure time sampling interval; and performing interpolation polynomial fitting according to the maximum exposure time and the exposure time sampling interval. Compared with a conventional mode of determining exposure time in industrial AOI quality inspection, the method can save a lot of manpower work; the detection step length and the exposure time are decoupled, so that the method is more flexible; the method can adapt to the influence of the inner wall roughness and the bottom roughness caused by the abrasion of a machining tool on imaging to a certain extent.

The invention discloses an industrial DR equipment automatic defect detection method and system based on deep learning, and relates to the technical field of industrial nondestructive testing, and the method comprises the steps: obtaining industrial DR imaging data of a to-be-detected workpiece under a predetermined imaging attitude, and constructing an original image set according to an imaging sequence; and for the industrial DR imaging data in the original image set, based on the change consistency of the pixel gray in the spatial neighborhood, executing spatial continuity analysis, forming an abnormal region in which the gray change is continuously distributed in the space, and determining the abnormal region as a continuous gray abnormal region. Spatial continuity analysis is carried out on industrial DR imaging data, a continuous gray abnormal area is formed and identified, and a main extension direction is further determined based on a spatial distribution form of the continuous gray abnormal area in an image coordinate system, so that directivity description parameters are introduced in an abnormal area level, and the accuracy of the abnormal area is improved. And the continuous gray-scale abnormal region is not processed only as a gray-scale abnormal object any more.

The utility model discloses an industrial CT imaging device. The industrial CT imaging device comprises a base, a first linear module, a second linear module, a third linear module and a first ray source. The first linear module is mounted on the base, the first linear module is provided with a first sliding table and a second sliding table which are located on the same sliding rail, the first sliding table is connected with a first driving part, and the second sliding table is connected with a second driving part; the second linear module is installed on the first sliding table and is in orthogonal connection with the first linear module on the horizontal projection plane, a rotary table is installed on the second linear module, and a clamping assembly is arranged on the rotary table; the third linear module is installed on the second sliding table and is parallel to the second linear module, a lifting module is installed on the third linear module, a support is installed on the lifting module, the support is provided with a plurality of assembling areas, and a ray detector is installed on one of the assembling areas; the first ray source is connected with the base, and the first ray source and the ray detector are distributed on the two opposite sides of the clamping assembly.

The application provides a kind of industrial CT scattering and beam hardening coupling artifact suppression method based on deep learning, belongs to the field of industrial CT image processing, for the problem that coupled artifacts cannot be accurately separated and corrected in industrial CT imaging, a beam hardening, scattering coupling artifact model based on real CT image artifact features is constructed, a simulated image and an actual image are mixed to construct a data set by a coupled model representation equation, and artifact suppression and image enhancement are completed by a long-short connection, structure doublet improved neural network, effectively removing multiple types of coupled artifacts and noise, this method is suitable for coupled artifact suppression of any complex structure actual CT image, and the practicability and generality of the method are better.

This invention relates to an in-situ high-temperature testing device, system, and method for liquid metal environments based on industrial CT. The device includes a column mounted on a base, with a clamp lifting mechanism and a clamp self-rotation mechanism on the column, capable of driving the sample on the clamp to complete up-and-down reciprocating motion and automatic rotation. The testing method includes: 1) sample installation; 2) sample heating; 3) sample fatigue testing; 4) sample rotational three-dimensional CT scanning; and 5) cyclic loading and continuous observation. This invention not only meets the requirements for high-temperature in-situ testing in liquid metal environments but also shortens the distance between the X-ray source and the sample, and improves the resolution of industrial CT imaging.

1. Name of the product in this design: Industrial Imaging Equipment. 2. Purpose of this design: for ultra-high-definition image detection. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The invention provides an industrial CT (Computed Tomography) pose parameter calibration method based on a microsphere motif, which relates to the field of industrial CT imaging and comprises the following calibration steps: acquiring perspective images of the microsphere motif at different positions; extracting circle center coordinates of a microsphere projection circle in the perspective image; calculating the coordinates of two projection points on the rotating shaft according to the circle center coordinates of the projection circle so as to calibrate the in-plane deflection angle of the detector; establishing a mathematical relationship model among pose parameters, model body parameters and projection image coordinates, and calibrating the distance between a radiation source and a rotating shaft of a rotating table and the distance between the radiation source and a detector; and establishing a mathematical relationship model among the circle center coordinates of the projection circle of the sphere a, the offset of the detector and the parameters of the industrial CT system, and realizing the calculation of the offset of the detector. The rotary table does not need to be rotated by too many angles, the influence of the motion error of the rotary table on the calibration result is avoided, and meanwhile the machining difficulty of the die body is reduced.

The application discloses a high-precision industrial CT imaging system geometric parameter correction method and system, which comprises the following steps: step 1, a phantom is arranged at the center of a rotating table of an actual cone beam CT, the distance between a jth marker point in the phantom and a selected marker point is D real in a space coordinate system; step 2, actual projection data (v ij ,w ij ) of the jth marker point at an ith sampling angle in a detector local coordinate system is determined; step 3, predicted projection data (v i (ζ j ),w i (ζ j )) of the jth marker point at the ith sampling angle in the detector local coordinate system in a circular trajectory cone beam mode is obtained; step 4, the mean square error between (v ij ,w ij ) and (v i (ζ j ),w i (ζ j )) is set as a target function, and an optimal geometric parameter vector of the jth marker point is obtained, wherein the geometric parameter vector comprises the distance D rec between the jth marker point and the selected marker point in the space coordinate system and the distance sod between a ray source and the center of the rotating table; and step 5, the corrected distance sod real between the jth marker point and the selected marker point in the space coordinate system is obtained by using D rec , D real and sod.