525 results about "Image Inspection" patented technology

The invention relates to a face depth forgery active defense method and device based on discrete wavelet transform, and relates to the technical field of image processing, and the method comprises the steps: carrying out the attribute editing of an original image and a disturbance-containing image through a depth forgery model, calculating the mean square error loss and structural similarity loss between the original image and the disturbance-containing image, different weights are endowed and fused into a total loss function; gradient information is obtained based on loss function back propagation, the optimal direction of disturbance application is determined, and an intermediate disturbance value is formed; low-frequency and high-frequency components are embedded into corresponding components of the disturbance-containing image through discrete wavelet transform, and then the image is reconstructed through inverse discrete wavelet transform; checking whether the number of iterations is reached or not, and if not, introducing a JPEG noise layer to continuously iterate and adjust disturbance; and if yes, outputting a final face image containing invisible disturbance information. According to the method, the robustness in the wavelet domain is fully utilized, and the resistance of disturbance to JPEG compression is improved on the premise of ensuring that the disturbance is invisible.

In some examples, one or more processors of an aerial vehicle access a scan plan including a sequence of poses for the aerial vehicle to assume to capture, using the one or more image sensors, images of a scan target. A next pose of the scan plan is checked for obstructions, and based at least on detection of an obstruction, the one or more processors determine whether a backup pose is available for capturing an image of the targeted point orthogonally along a normal of the targeted point. Responsive to determining that the backup pose is unavailable for capturing an image of the targeted point orthogonally along the normal of the targeted point, image capture of the targeted point is performed at an oblique angle to the normal of the targeted point.

A method for automatic registration of a patient for surgical navigation includes detecting a pose of a robot head with a robot camera by a tracking camera of a navigation system and following the robot camera; controlling and moving a robot arm such that the robot camera is directed to a region of interest of the patient, and creating an image; checking whether there is a visual connection between the tracking camera and robot head with the robot camera; detecting, when a visual connection is present, a pose of the robot head via the tracking camera, or detecting, when the visual connection is missing, interrupted or reduced, a pose of the robot head via a robot-kinematics tracking system; and executing a registration of the patient with respect to the navigation system. The registration method can be used with a surgical navigation system and a computer-readable storage medium.

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.

The invention relates to the technical field of high-voltage cable operation inspection, and provides a high-voltage cable operation inspection method and system based on online monitoring and intelligent inspection. An online monitoring system based on an artificial neural network algorithm is used for diagnosing the cable operation fault probability, and when the cable operation fault probability does not exceed a threshold value, the cable operation fault probability is detected; according to the method, image information of a corresponding cable is obtained, image inspection is further carried out on the position of the cable suspected to have a fault, image detection is carried out through an image defect diagnosis algorithm, a predicted value of the operation fault probability of the cable based on the image is obtained, and when the predicted value does not reach a predicted threshold value, the cable is detected. Sending a confirmation operation inspection signal to a cable operation inspection unit corresponding to the position information so as to remind the cable operation inspection unit to inspect and confirm whether a fault occurs in a cable area corresponding to the position information; and when the fault cannot be completely eliminated, the fault detection precision is improved, unnecessary inspection operation is reduced, and manpower and material resources are saved.

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.

To improve defect detection accuracy in a defect inspection based on a photographed image of a substrate.SOLUTION: A substrate inspection device that inspects a substrate on the basis of a photographed image of the substrate includes: a holding unit which holds the substrate; a light source unit which emits light onto the substrate held by the holding unit; a movement mechanism which moves the holding unit; an imaging unit which images the substrate by receiving reflected light or scattered light from the substrate held by the holding unit; and a control unit. The control unit executes: the step (A) which causes the imaging unit to receive the first light from the substrate held by the holding unit and image the substrate while moving the holding unit in the first direction; and the step (B) which causes the imaging unit to receive the second light different from the first light from the substrate held by the holding unit and image the substrate while moving the holding unit in the second direction opposite to the first direction.SELECTED DRAWING: Figure 5

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.

Provided are an image inspection device and an image processing method which are robust with respect to variations in image quality and with which it is possible to detect a defect or another abnormality with high accuracy. Provided is an image inspection device for comparing a first image with a second image and acquiring a difference between the images to inspect an abnormality that could be present in either the first image or the second image. The image inspection device comprises: an image quality feature amount extraction unit that extracts an image quality feature amount, which is a feature amount vector representing image quality for each partial region of the first image; an image quality correction unit that brings the image qualities of the first image and / or the second image relatively closer for each partial region on the basis of the feature amount vector obtained by the image quality feature amount extraction unit and the second image; and a comparison processing unit that compares any one of the images corrected by the image quality correction unit and the other image, or compares the corrected first and second images, to acquire a difference between the images. The image quality feature amount extraction unit includes a region division processing unit that divides the first image into partial regions in units larger than the size of a predetermined abnormality, and a feature amount extraction processing unit that extracts a feature amount vector representing the image quality of each partial region from the other partial regions of the first image.

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.

A horizontal well video detection phase indicating device disclosed by the present invention comprises a detection probe, support rods, a protection cone, a fixed seat, a bushing and a dial assembly, the detection probe is in threaded connection with a plurality of support rods, the other ends of the support rods are installed on the protection cone, one side of the protection cone is provided with the fixed seat, the fixed seat is installed on the support rods, and the bushing is installed on the fixed seat. A lining is fixedly connected to the fixing base, and a dial assembly is installed on the lining. According to the invention, the dial assembly is additionally arranged on the detection probe, and the dial assembly enables the turntable to always keep the 0-degree scale to point to the low gravity side of the shaft through the balancing weight, so that the problem that the target phase information of the shaft cannot be obtained when the video image in the horizontal section is lack of judgment basis is solved; the dial assembly can visually read phase information when horizontal section wellbore imaging detection is carried out, the target position wellbore phase accuracy of video imaging detection interpretation results is improved, and more complete wellbore target information is provided for follow-up operation measures and research analysis.

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.

To provide a fruit sorting device which enables reduction of burdens of a farm producer in harvesting and fruit sorting of fruit vegetables.SOLUTION: A fruit sorting device 100 according to an embodiment includes: a sorting part 10 including a body 11 including a plurality of test spaces 11R into which test objects are respectively placed, and discharge mechanisms each of which discharges the test object placed into the test space 11R to the outside of the body 11; storage parts 30A to 30C which store the test objects discharged from the test spaces 11R; an imaging part 20 which captures images of the test objects placed into the test spaces 11R; and a control unit 40 which performs tests of the test objects with the images of the test objects and causes the test objects to be discharged from the test spaces 11R according to the test results by the discharge mechanisms and stored in the storage parts 30A to 30C.SELECTED DRAWING: Figure 2

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 discloses a deep network-based visible light image inspection identification method for power transmission line hardware fittings, which introduces an innovative unmanned aerial vehicle inspection mechanism, realizes automatic feature extraction of targets in images by capturing visible light images of key equipment of a power transmission line and depending on an improved Faster RCNN algorithm, and improves the detection accuracy of the target features. And finally, intelligent identification of the visible light inspection image of the power transmission unmanned aerial vehicle is realized. The visible light image inspection recognition method for the power transmission line hardware fitting based on the deep network is suitable for hardware fitting picture detection with a poor shooting effect, is not easily influenced by a shooting background, light and noise, is high in robustness, and remarkably improves the accuracy of hardware fitting detection in a complex scene.

An authenticity determination support system includes an acquiring means, a checking means, and a presenting means. The acquiring means acquires an image of a determination target object from a user terminal. The checking means checks the image of the determination target object against images in image group information stored in a storing means that stores the image group information including an image of an authentic product and an image of a counterfeit thereof. In a case where the image group information including an image that matches the image of the determination target object is detected as a result of the checking, the presenting means displays support information including the detected image group information on a screen of the user terminal.

The invention provides a drinking water quality monitoring method and system, and relates to the technical field of water quality monitoring, and the method comprises the following steps: setting a plurality of sampling points in a multi-stage pipe network, and collecting drinking water samples; determining a first weight of the drinking water sample; obtaining a microscope sample of the drinking water sample; observing the microscope sample through a microscope to obtain a microscopic image; obtaining an image detection score according to the microscopic image; obtaining a drinking water quality visual detection score according to the image detection score and the first weight; obtaining the target drinking water sample passing the image detection, and detecting the content information of the harmful substances through a spectrograph; obtaining a drinking water quality spectrum detection score according to the content information and the first weight; and obtaining a drinking water quality score according to the quantity ratio of the target drinking water sample, the drinking water quality visual detection score and the drinking water quality spectrum detection score. According to the invention, the conveying process of the drinking water can be monitored in all directions, and the water quality condition of the drinking water can be evaluated comprehensively and accurately.

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 discloses a railway tunnel intelligent illumination management system, which comprises a selection module, a monitoring module and an inspection module, and is characterized in that tunnel identifiers along a railway are selected on an electronic map, monitoring data from a plurality of illumination monitoring lamps arranged in a railway tunnel are received, and alarm recording or / and popup display are / is carried out; the illumination monitoring lamps also shoot images in the railway tunnel, carry out image inspection, and generate dynamic simulation inspection by using the shot images. According to the system, safety monitoring can be carried out on the interiors of railway tunnels distributed in multiple places, intelligent dynamic inspection is achieved, and the accuracy, timeliness and safety of monitoring of the interiors of the railway tunnels are enhanced.

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.