300 results about "Image Inspection" patented technology

The invention relates to the technical field of rural image inspection and recognition, and discloses a multi-source image collaborative inspection and recognition analysis system and method for a digital rural area, and the method comprises the steps: collecting multi-source image data in real time; obtaining a plurality of characteristic parameters corresponding to each image data item in the image data set, and carrying out space-time registration and multi-scale fusion processing on the plurality of characteristic parameters of each image data item; performing target detection and identification analysis on the plurality of feature parameters in the fusion feature parameter set, and constructing an abnormal point identification model; setting a plurality of abnormal point change thresholds according to the inspection coordinate data set for classification processing to obtain a plurality of abnormal point categories; and setting a corresponding co-processing scheme according to the plurality of abnormal point categories, and setting early warning information corresponding to the change trends of the plurality of abnormal point categories based on the co-processing scheme. According to the invention, the intelligent degree and response efficiency of rural inspection are improved, and the safety and sustainable development of digital rural construction are effectively guaranteed.

The invention relates to the technical field of image processing, in particular to a mobile phone screen quality inspection method and system based on a screen picture inspection partition, and the method comprises the following steps: detecting partitions divided based on the surface of a mobile phone screen, recognizing a sudden change interval, analyzing the consistency of a gray gradient direction and an edge fitting vector, screening abnormal partitions, and extracting color and texture features. And evaluating deviation from a screen flatness curve, screening the subarea of which the response coverage area needs to be adjusted, and outputting a repairing and adjusting instruction set. According to the method, the image detection area is divided, and the abnormality is screened in combination with the gray slope and the edge deviation abrupt change, so that the recognition accuracy and the response speed are improved, the gradient direction and edge vector consistency are fused to enhance junction defect judgment, and the complex abnormality linkage screening is realized in combination with the color and texture features. The risk level is quantified based on the deviation flatness trend, and the functional diagram is linked to realize repair response scheduling, so that the detection reliability and decision pertinence are improved.

On the basis of determination by image inspection that an image defect is generated and a predetermined condition being satisfied, an instruction unit for issuing an image diagnosis instruction is displayed on a screen of an inspection result, and image diagnosis is executed in response to an operation on the instruction unit.

To provide an image inspection device and an image inspection method capable of obtaining an actual imaging angle with respect to a workpiece.SOLUTION: An image inspection device 1 comprises: a mirror rotating body 12; an imaging section 13; a positioning reference alignment section that is provided to the mirror rotating body 12 so as to rotate integrally with the mirror rotating body 12 to be imaged together with a workpiece; a drive section 14 that drives the mirror rotating body 12 rotationally; an imaging-processing section 151 that causes the drive section 14 to drive the mirror rotating body 12 rotationally, and causes the imaging section 13 to capture an image of the workpiece when the mirror rotating body 12 is positioned at a preset setting angle; and an imaging angle acquisition section 152 that acquires an imaging angle of a captured image corresponding to the setting angle on the basis of the alignment section appearing in the captured image.SELECTED DRAWING: Figure 1

The cutting device includes an imaging unit, a first processing unit, and a second processing unit. The photographing unit generates a photographed image by photographing some or all of the plurality of cut articles. The first processing unit sets a plurality of inspection regions in a captured image. The second processing unit inspects the appearance of each cut product included in the captured image on the basis of images included in each of the plurality of inspection regions in the captured image. The first processing unit executes a determination process for determining whether or not a portion of any side of a plurality of cut products is included in a predetermined number of pixels on the basis of the pixel values of the predetermined number of pixels continuously located in a first direction in a captured image. The first processing unit sets at least a part of the plurality of inspection regions by repeatedly moving positions of a predetermined number of pixels and executing determination processing.

The invention discloses a running water image inspection method, device and equipment and a medium. The method comprises the following steps: acquiring a to-be-processed pipeline image and inspection reference data corresponding to the to-be-processed pipeline image; averagely segmenting the to-be-processed pipeline image into N sub-images, and inputting the N sub-images into the image feature extraction model to obtain a feature map of the to-be-processed pipeline image; inputting the test reference data into the data feature extraction model to obtain data features of the test reference data; inputting the feature map and the data features into a pipeline image classification model to obtain a category label of the to-be-processed pipeline image; the classification label is real or forged; and according to the category label, determining an inspection result of the to-be-processed pipeline image. According to the embodiment of the invention, the method can automatically, comprehensively and accurately inspect the pipeline image based on the feature map of the pipeline image and the data features of the inspection reference data which can be used for auxiliary inspection, and determines whether the pipeline image is a real pipeline image or a forged pipeline image.

The invention belongs to the technical field of non-woven fabric flaw detection, and discloses a non-woven fabric surface flaw detection auxiliary device which comprises a supporting frame, a top plate is fixed to the surface of the supporting frame, an image inspection head body is fixed to the surface of the top plate, and a winding roller is rotationally arranged on the surface of the supporting frame. Feeding rollers are rotationally arranged on the two sides of the surface of the supporting frame, a non-woven fabric body is arranged on the surfaces of the feeding rollers, and the other end of the non-woven fabric body is arranged on the surface of a winding roller; when a non-woven fabric body is subjected to flaw detection through a lamp tube and an image detection head body, fibers can be received under the action of a rotating mechanism, and falling fibers are conveyed under the condition that the rotating mechanism rotates, so that the falling path of the fibers is changed, and under the suction action of an impurity removal mechanism, the defects of the non-woven fabric body are removed. In addition, due to the fact that the fibers are sucked through suction force, friction on the surface of the rotating mechanism can be reduced, and the practicability of the device is further improved.

The invention provides a BIM model-driven construction site quality acceptance method and equipment. The method comprises the following steps: constructing a high-precision semantic BIM model with a quality acceptance knowledge graph; generating a panoramic inspection planning route based on the high-precision semantic BIM model: based on the panoramic inspection planning route, operating panoramic image inspection equipment to execute field inspection so as to collect field panoramic video image data; performing position calculation on the scene panoramic video image data, and performing spatial alignment on the scene panoramic video image data and the high-precision semantic BIM model based on a position calculation result; based on a high-precision semantic BIM model and an alignment result of on-site panoramic video image data and a high-precision semantic BIM model space, detection and identification of quality problems of key components are carried out, and the typical problems that on-site inspection is not planned and intelligent identification is not focused are emphatically solved. And more optimized and more targeted on-site panoramic inspection and more targeted quality problem discovery are realized.

An image inspection apparatus includes a control unit configured to execute a model which is a segmentation model. The model includes an encoder part configured to extract a first feature from the inspection image data, a connection part configured to receive a second feature different from the first feature from at least one of layers in the encoder part, convert the second feature into a third feature, and supply the third feature, and a decoder part configured to upsample the first feature using the third feature. The control unit updates the parameters of the connection part and the parameters of the decoder part when executing machine learning of the model based on the training image data.

The invention relates to the technical field of mobile phone module shell detection, and discloses an image detection device for a mobile phone module shell, which comprises a first visual detection unit and a second visual detection unit connected with the first visual detection unit, the adjusting unit is connected with the first visual detection unit and is used for adjusting the acquisition areas of the first visual detection unit and the second visual detection unit; the first visual detection unit comprises a driving part connected with the adjusting unit, the driving part is provided with two output ends, and one output end is connected with the second visual detection unit; the plurality of first cameras are used for acquiring images of the mobile phone module shell; the acquisition assembly is connected with the other output end of the driving part, and the first camera is located on the acquisition assembly; according to the equipment, the distance and angle between the first camera and the second camera and the mobile phone module shell are adjusted to obtain multiple groups of data, and the multiple groups of data are screened and evaluated to complete image detection of the mobile phone module shell.

The invention discloses an automatic visual detection method and system for finished product quality, relates to the field of image detection, and ensures that any area on the surface of a product can be clearly imaged in at least one image by performing multi-angle synchronous image acquisition on the product so as to obtain complete surface information. Then, through image registration, an illumination difference image (a pixel variance image and an average brightness image) is generated, and the illumination change itself is used as an analyzable feature; and finally, splicing the original image set and the illumination difference image into multi-channel input, and sending the multi-channel input to a deep learning network. The network can effectively distinguish normal pixel fluctuation caused by illumination change and abnormity caused by real defects from fused high-dimensional information, and finally realizes accurate detection of the defects of the high-reflection complex curved surface finished product.

A method for acceptance inspection audit is implemented by a computer that stores original image data sets. Each original image data set corresponds to an object image, and an image height-width data set of the object image that corresponds to one of image height-width categories. The method includes steps of: A) based on the image height-width data sets, counting a number of occurrences of each of the image height-width categories; B) obtaining, as a target image height-width category, one of the image height-width categories that has a greatest number of occurrences; C) for each original image data set in a group of to-be-inspected data sets, adjusting the object image based on the target image height-width category, thereby obtaining an adjusted-original image data set; and D) obtaining at least one image inspection result based at least on the adjusted-original image data sets thus obtained respectively for the original image data sets.

The present invention relates to an image inspection device and a setting method for an image inspection device. In order to enable easy additional learning of non-defective product images or defective product images in both the setting mode and the operation mode. A designation related to whether to additionally learn the inspection object image displayed on the operation mode screen as a non-defective product image or a defective product image is received. The discriminator generation unit additionally learns the inspection object image designated as the additional learning object as a non-defective product image or a defective product image, and updates the discriminator.

To provide an image inspection device capable of improving convenience in setting an inspection-related area.SOLUTION: An image inspection device comprises: an acquisition part which acquires a first image which is a read image of an inspection object medium on which printing has been applied, and a second image which is a reference image serving as a reference for inspection; and an inspection part which performs an image inspection on a printing region of the inspection object medium according to the first image and the second image, and excludes an end region of the inspection object medium from the image inspection.SELECTED DRAWING: Figure 9

The utility model provides a 3D5S image inspection device of a gravity type testing machine, which relates to the technical field of semiconductor testing and comprises a supporting seat, the supporting seat is provided with a lifting driving assembly, the lifting driving assembly is provided with a rotary driving assembly, and the rotary driving assembly is provided with a plurality of suction nozzle assemblies. A 3D 5S image testing assembly is arranged below the suction nozzle assembly, a feeding rail assembly is arranged on one side of the rotary driving assembly, a discharging rail assembly is arranged on the other side of the rotary driving assembly, and the feeding rail assembly and the discharging rail assembly are both used in cooperation with the rotary driving assembly. The device has the beneficial effects that the rotary driving assembly drives the rotary disc to periodically rotate and lift, so that the suction nozzle assembly sucks the component from the feeding track assembly and rotates to the 3D5S image testing assembly for detection, and after detection is finished, the rotary disc drives the suction nozzle assembly to rotate to the discharging track assembly, so that the component enters the discharging track assembly for discharging, and therefore, the detection efficiency is improved. Therefore, the component detection efficiency is improved.

To provide an image inspection device and an image inspection method capable of stabilizing adjustment precision of focusing.SOLUTION: An image inspection device 1 comprises: a photographing section 15; a focus confirmation tool 13 that is disposed in a photographing area A11 before a workpiece to be inspected and is used to previously confirm focusing of photographing while a part facing a side of the photographing section 15 when being disposed in the photographing area A11 becomes a confirmed section in a shape in which the position in the depth direction of a field depth of the photographing section is changed in steps; and a focus adjustment section 171 for adjusting focusing such that a target section corresponding to a workpiece in the confirmed section is included in a range of the depth of field on the basis of a tool photographed image obtained by photographing the focus confirmation tool 13.SELECTED DRAWING: Figure 1

This item is a housing for equipment such as devices for inspecting cylindrical motor cases and metal structural components such as piping. The four parts A, B, C, and D attached to the housing shown in the reference diagram are as follows: (A) Touch panel: Used for operating the entire device and setting parameters for movable parts. (B) Center button: Used for simultaneous two-handed start operation and emergency stop operation of the device. (C) Display: Used to display image inspection results and inspection data. (D) Keyboard and mouse: Used for setting image processing parameters.

An image inspection apparatus (100) that compares a read image generated by reading a recording medium on which an image is formed with a reference image to detect misregistration of an image formation position on the recording medium, the apparatus including a controller (81) that: aligns an image included in the read image and an image included in the reference image; and detects the misregistration of the image formation position based on a deviation between a reference position in the read image and a reference position in the reference image in an aligned state. The controller selects a reference position used for detecting the misregistration from reference positions included in the read image and the reference image based on a position of an area in which an image is formed on the recording medium.

An X-ray inspection apparatus includes an irradiation unit configured to irradiate a plurality of objects with X-rays, a detection unit configured to detect X-rays transmitted through the objects or X-rays reflected by the objects, a generation unit configured to generate an image for inspecting the number of objects based on the X-rays detected by the detection unit, and an inspection unit configured to inspect the number of objects based on the image. The generation unit generates area output information obtained using a learning model with the image as an input to identify areas of the objects in the image and processed information obtained by performing image processing on the image. The inspection unit calculates the number of objects based on the area output information and the processed information.

The invention discloses a wafer adhesion testing method, which comprises the following steps: first, placing the wafer at the center of a first adhesion disk for adsorption and fixation; second, performing image inspection on the wafer with a macroscopic detection camera, and continuously adjusting the angle of the wafer with the first angle adjustment seat in cooperation with the second angle adjustment seat during the inspection; third, after the macroscopic inspection, an electric telescopic rod lifts the bottom of the wafer through a lifting block, moves the wafer and places the wafer above a top block; fourth, using an adjustment wheel to make the center of the wafer, the center of the second adhesion disk and the lens of a microscopic detection camera be on the same vertical line, and then fixing the wafer through a vacuum adsorption hole on the second adhesion disk; and fifth, aligning a probe with the center point of the wafer, while the probe contacts the contact point on the grain, and driving the power supply to test the electrical characteristics of the wafer and record the results, and unqualified grains will be marked with a needle mark, thereby improving the inspection efficiency while ensuring the inspection quality of the wafer.

To efficiently inspect images.SOLUTION: An image inspection apparatus comprises: an acquisition unit 51 which acquires image data to be subjected to image formation; a reading unit which reads an image of image data formed on a recording medium and outputs read data; and an inspection unit 53 which is operable in a first mode in which first inspection data is generated on the basis of the image data and the read data output by the reading unit is compared with the first inspection data and in a second mode in which the read data output by the reading unit upon reading a first image is stored in a storage device as second inspection data, and the read data output by the reading unit upon reading a second image is compared with the second inspection data. The inspection unit 53 switches between the first mode and the second mode on the basis of a remaining storage capacity of the storage device.SELECTED DRAWING: Figure 4

This invention discloses an industrial material inspection method and system based on feature extraction and contrast enhancement, belonging to the field of image inspection technology. It includes: S1, acquiring the transmitted signal using a digital flat panel detector and generating an original digital image based on the differences in X-ray absorption by different materials or defects; S2, performing uniformity correction and normalization enhancement on the original digital image, and achieving preliminary differentiation of different material regions; S3, dividing the original image data into processing domains based on the preliminary differentiation results, and performing differentiated enhancement processing based on the local feature attributes of each processing domain to generate a binary feature image. By integrating X-ray penetration imaging, multi-dimensional image enhancement, and a deep learning-driven intelligent rating system, this invention fundamentally solves the key technical bottlenecks in traditional industrial material inspection, such as inconsistent image quality, lack of material identification, and strong subjectivity in rating, achieving an automated, intelligent, and objective upgrade in industrial material defect detection.

An image inspection apparatus includes an image reader that reads an original image formed on a recording material based on a print job and generates a read image, and a hardware processor that analyzes the read image and performs an image inspection, wherein the hardware processor: acquires the read image from the image reader, detects an edge from the read image, and excludes a region near the edge from a target of the image inspection; performs a predetermined filter process on the read image after the exclusion process to generate a first reference image; compares the read image after the exclusion process with the first reference image to generate a first comparison image; and binarizes the first comparison image using a predetermined threshold to detect points where a specific abnormality has occurred, and outputs a detection result.

To provide an image inspection device, an image inspection method and an image inspection program which can properly inspect a printed matter by printing requiring a reference image to be pre-registered, while improving productivity in inspecting a printed matter by printing not requiring the reference image to be pre-registered.SOLUTION: An image inspection device 300 comprises an image formation part 330, a reference image generation part 380, and an image inspection part 350. The image formation part 330 forms an image on a recording medium on the basis of obtained image data. The reference image generation part 380 generates a reference image that is used in inspecting the image formed on the recording medium. The image inspection part 350 inspects the image formed on the recording medium, on the basis of the reference image. The image inspection device 300 has a first inspection mode in which the reference image is registered and a second inspection mode in which the reference image is not registered, at a predetermined timing in a step in which the image formation part 330 forms the image that is inspected by the image inspection part 350.SELECTED DRAWING: Figure 2

The disclosure provides an image management method, server and image capture device. The method performs image inspection operations on uninspected second images among multiple first images arranged in chronological order. The operations include: identifying target objects and determining their orientations; evaluating the completeness of various parts of the target objects based on their orientations; and generating corresponding completeness codes. Finally, the image with the highest completeness code is selected as the target image for output. This method effectively filters out the most suitable images for person re-identification, thereby enhancing overall system performance.

A closing device (10) for closing a container (52), in particular a pharmaceutical or cosmetic container, with a cap (48), wherein the closing device (10) comprises a holding device (12) and a crimping device (14), wherein the holding device (12) is configured to hold the container (52) at a crimping position (62), and wherein the crimping device (14) is configured to crimp the cap (48) onto the container (52) at the crimping position (62), wherein the holding device (12) is configured to rotate the container (52) at the crimping position (62) about a vertical axis, characterized in that the closing device (10) further comprises an optical inspection device (16) which is configured to inspect one or more properties of the container (52) and / or the cap (48) at the crimping position (62).wherein the control device (16) comprises a camera system (17), wherein a camera (40, 40') of the camera system (17) is configured to successively capture a plurality of images of the closure cap (48) and / or the container (52) at the crimping position (62), while the holding device (12) rotates the container (52) at the crimping position (62) about the vertical axis, wherein the control device (16) is configured to check one or more properties of the container (52) and / or the closure cap (48) based on the plurality of images.

To prevent deterioration in measurement accuracy due to the influence of stray light in a technique for inspecting an image recorded on a print medium by using an imaging part and a colorimetric part.SOLUTION: In the image inspection apparatus and the printing apparatus according to the aspects of the invention, the printing medium is supported by being stretched between the first roller and the second roller. An imaging unit that images an imaging region by causing illumination light to be incident on a portion of the printing medium wound around the first roller and receiving reflected light from the imaging region on which the illumination light is incident, a colorimetry unit that performs color detection of a color detection region by causing the illumination light to be incident on a portion of the printing medium wound around the second roller and receiving light reflected from the color detection region on which the illumination light is incident and incident on a light receiver, and a light shielding unit that is disposed between the imaging unit and the light receiver on a first main surface side of the printing medium stretched between the first roller and the second roller and shields light from the imaging unit toward the light receiver.SELECTED DRAWING: Figure 7

The invention relates to the technical field of artificial intelligence, and provides an eosinophilic gastroenteritis typing system and method based on multi-modal data, and the method comprises the steps: obtaining a digestive endoscopy image, an ultrasonic endoscopy image, a CT examination image and clinical manifestation data of a to-be-detected person collected in the same time period; the gastrointestinal mucosa lesion state is recognized through a digestive endoscopy image and is represented by numerical features; identifying the abnormal thickening condition of each film layer structure of the gastrointestinal wall through an ultrasonic endoscope image, and representing the abnormal thickening condition by numerical features; lesion hierarchical distribution is judged through an ultrasonic endoscope image, and numerical feature representation is carried out; determining seroperitoneum and intestinal wall thickening conditions through a CT examination image, and performing numerical characteristic representation on the seroperitoneum and intestinal wall thickening conditions; clinical symptom features are obtained through the clinical manifestation data and are represented by numerical features; generating a feature vector based on multi-modal data by using each numerical value feature representation; and inputting the feature vectors into a dynamic typing prediction model to realize the typing prediction of eosinophilic gastroenteritis, thereby improving the accuracy of auxiliary diagnosis and evaluation.

The invention relates to an image inspection apparatus. The image inspection apparatus includes: an imaging section configured to generate a plurality of frame images arranged in a time sequence; an inspection execution section configured to execute inspection processing of an object appearing in the plurality of frame images using a machine learning model to output an inspection result; and an inspection setting unit for setting the inspection execution unit. The machine learning model includes a feature extraction unit and a determination unit that outputs an inspection result on the basis of the feature amount. The inspection setting section receives a selection of the first image and determines a threshold value. When it is determined that the threshold value exists between a first score based on the feature amount extracted from the first frame image and a second score based on the feature amount extracted from the second frame image, the inspection execution unit outputs an inspection trigger.