192 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.

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 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.

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

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.

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.

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.

To provide a composite metal foil in which a second copper layer is laminated on a nickel layer and which can be suitably used for a printed wiring board because a circuit can be formed by selective etching, the contrast between different kinds of metals is clear and can be easily identified, and erroneous detection and detection omission of a circuit pattern in image inspection and displacement in the case of multilayering hardly occur.SOLUTION: A composite metal foil comprising at least one layer structure of a first copper layer / a nickel layer / a second copper layer, wherein an absolute value of a difference between a lightness L * Cu value of a surface of the second copper layer and a lightness L * Ni value of a surface of the nickel layer on which the second copper layer is laminated is 15 or more.SELECTED DRAWING: Figure 1

The invention discloses an automatic feeding and discharging X-ray DR / CT detection device for a carbon-carbon composite material. The automatic feeding and discharging X-ray DR / CT detection device comprises an X-ray tube lifting and moving mechanism, a detector lifting and moving mechanism, a high-precision rotary table moving mechanism, a feeding assembly line, a discharging assembly line, a reversing mechanism, a rotary moving detection assembly line and a workpiece tool tray. The feeding assembly line conveys assembly line workpiece tool trays to the rotary movement detection assembly line, the rotary movement detection assembly line moves to a detection position to conduct DR detection on workpieces, CT imaging detection is conducted in situ after defects are found, the double-station detection technology combining the automatic assembly line feeding and discharging technology and the DR / CT detection technology is adopted, large workpieces can be detected, and the detection efficiency is improved. Compared with traditional CT detection, the device is faster and more convenient, achieves the purpose of automatically completing detection through one-time feeding, reduces frequent feeding and discharging of operators, greatly reduces the labor intensity, reduces the number of times that the operators go in and out of a detection room, saves time, greatly improves the detection efficiency, and is suitable for wide popularization.

Provided are an image inspection device and an image inspection method that are capable of suppressing inspection omissions due to overexposure. An image inspection device (1) is characterized by comprising: an imaging unit (15); a first illumination unit (14) that emits illumination light from an imaging direction (D14) to an imaging area (A11); a second illumination unit (16) that emits background light through the imaging area (A11); an imaging processing unit (171) that causes the imaging unit (15) to continuously perform first imaging processing for imaging a workpiece while the same is irradiated with both the illumination light and the background light, and second imaging processing for imaging the workpiece while the same is irradiated only with the background light; and an inspection processing unit (172) that sets a potential overexposure area on the basis of a first captured image obtained through the first imaging processing, and that performs image inspection on the potential overexposure area on the basis of a second captured image obtained through the second imaging processing.

To provide an image inspection device, an image inspection method and an image inspection program which can further shorten a time required in processes ranging from generation of a reference image to image inspection in comparison with in a conventional technique.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 for inspecting the image formed on the recording medium, on the basis of the obtained image data. 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 performs generation of the reference image and formation of the image on the recording medium in parallel.SELECTED DRAWING: Figure 2

To provide an electronic apparatus capable of accurately detecting the presence or absence of misalignment of a heat transfer sheet though image inspection.SOLUTION: An electronic apparatus according to the present invention includes: a housing; a plurality of bus bars; and heat transfer sheets disposed on a bottom surface of an accommodation portion the housing, and sandwiched between the housing and the bus bars. Therein each of the heat transfer sheets has a detection point, and is disposed such that two sides constituting outline of the heat transfer sheet are aligned with two intersecting reference lines of the housing, and the detection point is located in a position that does not overlap with the bus bars in a top view, so as to eliminate a need to accurately detect positions of edges of the heat transfer sheet, and misalignment of the heat transfer sheet can be accurately detected through image inspection.SELECTED DRAWING: Figure 1

An image inspection apparatus includes a learned neural network storage storing a neural network that previously learns weighting factors between input, intermediate and output layers, and an inferer determining failure / no-failure of a workpiece and classify the workpiece to classes based on an image of the workpiece. The inferer performs first and second inferences. In the first inference, the inferer determines failure / no-failure of the workpiece based on failure / no-failure feature quantities that are obtained by providing the workpiece image to the neural network and a failure / no-failure determination boundary. In the second inference, the inferer define a classification boundary to be used to classify an inspection workpiece to the classes in a feature quantity space of the neural network based on classification feature quantities that represent the different-type classification workpiece images, and classifies a workpiece to the classes based on classification feature quantities of an image of the workpiece and the classification boundary.

The invention relates to the technical field of image detection, and provides detection equipment which comprises a detection table, a controller and at least one test assembly. At least one mounting part is arranged on the detection table and is used for mounting to-be-detected image equipment; the at least one test assembly and the at least one mounting part are arranged correspondingly; the imaging end of the imaging device faces the test assembly and obtains a detection image of the test assembly. The controller is electrically connected with the to-be-detected image equipment, and the controller analyzes a detection image acquired by the to-be-detected image equipment. The detection equipment can meet the detection requirements of various different image equipment and detect a plurality of image equipment at the same time, so that the detection efficiency is improved.

A portable information handling system hinge is tested for wear to determine reuse or recycling by subjecting the information handling system to an acceleration and capturing a visual image of hinge movement in response to the acceleration. Excessive hinge wear is detected when housing movement exceeds a threshold distance or fails to achieve threshold dampening effect. After detection of hinge wear, when a hinge has sufficient torque for use in a selected of plural information handling system platforms, the hinge is reused, otherwise the hinge is broken down and recycled.

This invention provides a three-dimensional radar vision inspection method and system. The method first performs two-dimensional image inspection on the target object to preliminarily determine its material properties, and then sends a first electromagnetic wave to the target object to perform three-dimensional modeling. Next, material parameters are assigned to the target model, and electromagnetic wave propagation simulation is performed to obtain a simulated radar waveform. Ray tracing measurements are then performed on the target object using radar to obtain a measured radar waveform. The simulated radar waveform and the measured radar waveform are compared. If the difference between the two is within a first preset range, the material of the target object matches the material corresponding to the assigned material parameters. If the difference is still within the first preset range, the material parameters are updated, and the above steps are repeated. This inspection method can not only acquire the three-dimensional morphological information of the target object but also determine its surface material properties, overcoming the limitations of existing technology systems and providing comprehensive object recognition and material analysis capabilities.

To efficiently perform learning by simplifying labeling.SOLUTION: A setting receiving unit 13b displays a target image area for displaying a first image area corresponding to a first tool and a second image area corresponding to a second tool identifiably based on a single image when receiving a setting for an inspection program including the first tool to be executed in the first image area and the second tool to be executed in the second image area, and displays a setting screen including a label information area for displaying a first label corresponding to the first image area and a second label corresponding to the second image area, accepts designation of a first label related to the first image area and designation of a second label related to the second image area, trains a first model related to the first tool with a first data set including a combination of a single image and a first label, and trains a second model for a second tool with a second data set including a combination of a single image and a second label.SELECTED DRAWING: Figure 2

An image inspection apparatus capable of detecting fine defects without excessively increasing the resolution of an image input to a machine learning segmentation model. The image inspection apparatus includes an information generation unit that generates defect information based on an annotation that specifies a defect region in a training image, a training execution unit that trains a machine learning segmentation model, and an inspection execution unit that executes the trained machine learning model. The training execution unit determines whether to divide the training image according to a detection sensitivity setting of the defect region, and when division is required, the training execution unit divides the training image in a predetermined batch size and inputs the divided training image to the machine learning model.