367 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.

A mounting machine according to the present invention has a function for automatically determining the positions of measurement points for measuring the substrate height of a substrate on which a component is mounted. The mounting machine comprises an imaging device, an inspection device, and a determination device. The imaging device images, on the basis of a preset imaging condition, temporary measurement points disposed at temporary positions on the substrate. The inspection device inspects the temporary measurement points and the surrounding situation thereof by using a captured image of each of the temporary measurement points, and determines the suitability of the positions of the temporary measurement points. The determination device determines the positions as measurement points when the inspection device has determined that the positions of the temporary measurement points are suitable, and does not determine the positions as the positions of the measurement points when the inspection device has determined that the positions of the temporary measurement points are not suitable.

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

An image inspection system includes a processor and an inspection execution unit that performs an image inspection of a printed matter, in which the processor is configured to acquire first position information that is information on a position of the image inspection set in image data and to acquire second position information that is information on positions of the respective image data in data for printing in which the plural image data are arranged, and the inspection execution unit performs the image inspection of a printed matter on which the data for printing are printed using the first position information and the second position information.

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 present invention discloses a method for fusing infrared and visible light images of power transmission and transformation equipment inspection, S1: acquiring infrared images and visible light images of power equipment, constructing an image data set of power equipment, and dividing it into a training set and a test set; S2: constructing an infrared and visible light image fusion network model EIVFusion; S3: using the infrared images and visible light images of power equipment in the training set to train the infrared and visible light image fusion network model EIVFusion, and obtaining a trained infrared and visible light image fusion network model EIVFusion; S4: inputting the infrared images and visible light images of power equipment in the test set into the trained infrared and visible light image fusion network model EIVFusion to obtain a fused image. The present invention can well extract and fuse the features in visible light images and infrared images, and can realize high-performance fusion of infrared images and visible light images of power transmission and transformation equipment inspection.

An X-ray inspection device includes a conveying unit, an X-ray irradiation unit, an X-ray detection unit, and a control unit configured to inspect whether foreign matter is included in an article based on an X-ray transmission image. The control unit performs a first inspection of using a predetermined threshold value to inspect whether the foreign matter having a lower attenuation rate of X-rays than the article is included in the article, performs a second inspection of using a machine learning algorithm to inspect whether the foreign matter is included inside the article, and determines that the foreign matter is included in the article in a case where the foreign matter common to inspection results of the first inspection and the second inspection is included in the article.

The invention relates to the technical field of power transmission line monitoring, in particular to a power transmission line image inspection system based on machine learning, which comprises an acquisition layer, a transmission layer, a receiving layer, a scheduling layer, an inspection layer and an analysis layer. According to the invention, when the division of the inspection precision grades of the expected sites of the to-be-inspected areas is completed, whether the operation parameters of the acquisition layer are qualified is determined based on the number statistical result of the inspection precision grades, and when the operation parameters of the acquisition layer are determined to be abnormal, the operation parameters of the acquisition layer are automatically adjusted, so that the inspection efficiency of the power transmission line is improved.

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 present invention relates to a method and device for active defense against deep fake face based on discrete wavelet transform, and to the field of image processing technology. The method comprises: using a deep fake model to edit the attributes of the original and disturbed images, calculating the mean square error loss and structural similarity loss between the two, and merging them into a total loss function after assigning different weights; obtaining gradient information based on the back propagation of the loss function, determining the optimal direction of the disturbance application, and forming an intermediate disturbance value; embedding low-frequency and high-frequency components into the corresponding components of the disturbed image through discrete wavelet transform, and then reconstructing the image through inverse discrete wavelet transform; checking whether the number of iterations has been reached, if not, introducing a JPEG noise layer to continue iteratively adjusting the disturbance; if so, outputting a face image containing invisible disturbance information. The present invention makes full use of the robustness in the wavelet domain, and improves the resistance of disturbance to JPEG compression while ensuring that the disturbance is invisible.

The invention discloses a quality evaluation method and device for an image diagnosis report and a storage medium. The quality evaluation method comprises the steps that the diagnosis report corresponding to image inspection of a target object and an audit report corresponding to the diagnosis report are determined; determining different first text information in the diagnosis report and the audit report, and generating first prompt information based on the first text information; identifying the first prompt information by using a pre-trained difference analysis model, and determining error information corresponding to the first text information; when it is determined that the target difference type contains diagnosis type errors, grading the diagnosis type errors based on a preset disease grade library, and determining a corresponding grading result; and outputting a quality evaluation result of the diagnosis report by using a difference analysis model based on the error information and the grading result.

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.

An image inspection system includes a processor and an inspection execution unit that performs an image inspection of a printed matter, in which the processor is configured to acquire first position information that is information on a position of the image inspection set in image data and to acquire second position information that is information on positions of the respective image data in data for printing in which the plural image data are arranged, and the inspection execution unit performs the image inspection of a printed matter on which the data for printing are printed using the first position information and the second position information.

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 present invention relates to the technical field of transmission line monitoring, and in particular to a transmission line image inspection system based on machine learning, including an acquisition layer, a transmission layer, a receiving layer, a scheduling layer, an inspection layer, and an analysis layer. The inspection accuracy levels of each expected site are divided based on the inspection results of the inspection device. When the division of the inspection accuracy levels of the expected sites in each area to be inspected is completed, it is determined whether the operating parameters of the acquisition layer are qualified based on the statistical results of the number of each inspection accuracy level. When it is determined that the operating parameters of the acquisition layer are abnormal, the operating parameters of the acquisition layer are automatically adjusted, improving the inspection efficiency of the transmission line.

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 enable accurate image inspection of a drawing state of an object that is a drawing object.SOLUTION: An inspection device 500 includes: a storage part 513 for storing an inspection parameter for determining quality of a drawing state relating to information drawn to an object; a quality determination part 514a for determining quality of the drawing state relating to the information drawn to the object on the basis of an inspection image generated by an imaging part 511 and the inspection parameter; optical measurement sensors 30, 31 for receiving light from the object and generating a measurement value relating to the position or the movement of the object on the basis of the received light; and a determination part 514b for determining whether the position or movement of the object is outside the inspection object on the basis of the measurement value generated by the optical measurement sensors 30, 31. The quality determination part 514b determines that the drawing state is defective when the determination part 514b determines that the position or movement of the object is outside the inspection object.SELECTED DRAWING: Figure 52

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.