27 results about "Digital image analysis" patented technology

The invention belongs to the technical field of image processing, and discloses a remote digital image analysis cooperation system. The virtual diagnosis module is used for collecting a continuous pathological section sequence and carrying out space registration to obtain a registration section; the model building module is used for performing three-dimensional voxel reconstruction on the registration slices to obtain a three-dimensional voxel reconstruction model, and performing semantic enhancement to obtain a three-dimensional pathological voxel model; the collaborative interaction module is used for generating virtual avatars of G experts based on the VR technology, labeling the three-dimensional pathological voxel model and obtaining space anchor point labeling data of the experts; the graph driving module is used for constructing a structured semantic tree according to the space anchor point annotation data, detecting annotation conflicts and obtaining an annotation conflict detection result; the conflict resolution module is used for performing conflict resolution on the marking conflict detection result to obtain a consensus suggestion; the collaborative efficiency and conclusion reliability of remote diagnosis are improved, and a systematic solution is provided for precise diagnosis of complex pathological cases.

The invention relates to the technical field of image processing, and discloses a stamping part stamping forming quality detection method, which comprises the following steps: acquiring a surface digital image of a stamping part, analyzing the surface curvature and the material thickness change gradient of the stamping part, and generating a space prior weight map; calculating the structure tensor of a pixel point, and determining the orientation and axial length ratio of an elliptical sampling neighborhood; pixel point sampling is carried out along the elliptical sampling neighborhood to obtain an initial three-valued mode code; a global feature histogram is constructed, the contribution degree is accumulated to the statistical unit, and the contribution degree is the corresponding weight value of the pixel point in the spatial prior weight map; all the global feature histograms are cascaded to generate cascaded feature vectors; and inputting the cascade feature vector into a support vector machine classification model, and judging whether the stamping part to be detected is qualified or not. According to the method, the space prior weight map is introduced, the prior knowledge of the punch forming process is fused into the feature extraction process, so that the detection focuses on the defect high-incidence area, the extracted features are more targeted, and the detection accuracy is improved.

The invention discloses a large-scale visualized direct shear test device and method for geosynthetics. The device comprises a main frame, an upper shear box, a lower shear box, a normal cyclic loading system, a horizontal cyclic shear loading system, a data acquisition system and a visualized monitoring system. The direct shear test device is characterized in that the direct shear test device can perform normal and horizontal cyclic loading at the same time, and normal stress with different frequencies and amplitudes can be applied according to needs to simulate a test of the characteristics of the reinforcement-soil interface under the cyclic loading effect; one side wall of the upper shear box and one side wall of the lower shear box are transparent observation windows, and a high-speed camera and a digital image analysis method are combined, so that the shear band evolution process can be visually observed and quantitatively analyzed; the shear box is large in size, and the size effect is effectively overcome. According to the invention, the interface characteristics under the cyclic load effect in the road engineering can be reflected more truly and comprehensively, the size and the function of the shear box are comprehensive, and the interface mechanical characteristics and the interaction mechanism under various working conditions can be simulated.

The invention relates to the technical field of nondestructive testing of low-carbon steel, and particularly discloses a thermal double-sensitive composite coating as well as a preparation method and application thereof. The thermal double-sensitive composite coating comprises a stress sensitive fluorescent layer and a thermochromic layer, the stress sensitive fluorescent layer adopts core-shell hybrid particles with a force-induced fluorescence enhancement effect as key functional filler, and the thermochromic layer adopts an IPN-based irreversible thermochromic material as a core functional material. The stress-sensitive fluorescent layer and the thermochromic layer are prepared from novel self-made functional materials, so that the thermal double-sensitive composite coating has the functions of high-sensitivity signal sensing, optical enhancement and permanent recording, and is assisted by a load excitation and digital image analysis process; stress-temperature coupling field information excited by the deep defect under the load is converted into a visual signal which is high in strength, high in anti-interference performance and capable of being recorded permanently, and accurate positioning, quantification and classification of the defect are achieved.

Techniques for scanning physical media on physical items and providing information about those physical items are provided. In one technique, a digital image that is generated by a mobile device and that indicates a list of ingredients in an item is identified. Text that contains the list of ingredients is identified within the digital image. It is determined whether a particular ingredient in the list of ingredients satisfies one or more criteria. In response to determining that the particular ingredient satisfies the one or more criteria, the digital image is modified by causing a portion, of the text within the digital image, that corresponds to the particular ingredient, to be highlighted while the digital image is displayed on a screen of the mobile device. In a related technique, the mobile device performs all the steps, whereas in another technique, a remote server performs one or more of the steps.

The invention provides a wound surface area automatic calculation method, device and system and a storage medium. The wound surface area automatic calculation method comprises the following steps: S1, collecting a digital image containing a scald wound surface through a camera device, shooting the image in a non-real-time manner, and uploading the image to an attached standard ruler; and S2, during real-time measurement, measuring the distance between the wound surface and the camera, calculating the radius of a picture shot by the camera device by using a trigonometric function, and further calculating the shooting area corresponding to the shot picture. And calculating the number of pixel points in a unit area according to the pixels of the shot picture. During non-real-time shooting, the number of pixels corresponding to the unit length of the standard ruler is measured, and the total area of the image is calculated according to the proportional relation between the actual size of the unit length and the number of the pixels. The wound surface area automatic calculation method, device and system and the storage medium provided by the invention have the advantages that the operation is simple and convenient, the result is objective, accurate measurement of the scald area is realized through digital image analysis, and the clinical evaluation accuracy can be remarkably improved.

The present application is directed to identifying a gender of a chick. A method includes: causing a chick to transition along a path that is associated with a stimulus for provoking an open stance by the chick; obtaining one or more images of the chick in the open stance; determining one or more gender-related features of the chick based at least in part on the one or more images; and determining a gender of the chick based in part on the one or more gender-related features. One or more portions of the method can include any various machine learning techniques, such as supervised machine learning and / or unsupervised machine learning. For example, a supervised machine learning approach can be employed to train a neural network to identify a pose of a chick, identify gender-related features associated with the chick's wing, and / or assess the gender-related features for making a gender determination.

A system and method that identify a person at a bank branch, obtain information about the person, tailor certain bank products and services for the person based on the information about the person and present the tailored products and services to the person. The method includes taking images in the bank branch including images of bank branch customers, processing the images provided by the imaging system using a machine learning model, identifying a particular person in the images that is a customer of the bank, processing data and information about the identified person using the machine learning model, identifying bank products and services that are tailored to the identified person based on the processed data and information using the machine learning model, and providing information about the bank products and services to the bank branch in real time while the identified person is still at the bank branch.

The present invention relates to systems, methods and products for analyzing digital images, in particular digital pathology images.

The invention relates to a method for detecting structural defects of a wrapped yarn comprising a core formed of parallel fibres, whereby the core is bound together by a fibre wrapping layer comprising wrapping fibres and wild fibres, wherein an image of the moving yarn is captured by at least one optical yarn sensor over at least a part of the yarn length, whereby the optical yarn sensor comprises at least one row of radiation sensitive elements and at least one radiation source, and the optical sensor is connected to an electronic device equipped with software, whereby the captured yarn image is processed by a digital image analysis method to obtain data about the yarn surface structure, based on the obtained data, changes of the yarn surface structure along the yarn length are evaluated, these changes of the yarn surface structure are compared to preset criteria, and if these changes of the yarn surface structure exceed these preset criteria, the relevant position of the yarn is determined as the occurrence of a yarn structural defect. Furthermore, the invention relates to an apparatus, a computer program and a computer readable medium for carrying out the method.

This invention proposes a feature extraction method for texture images, belonging to the field of digital image analysis and image classification technology. The feature extraction method includes: inputting the texture image into a feature extractor based on the Vision Mamba architecture to extract a high-level feature map of the texture image; performing spatial domain processing and frequency domain processing on the high-level feature map in parallel to obtain a spatial feature map and a frequency feature map, respectively; and fusing the spatial feature map and the frequency feature map through a bidirectional cross-attention mechanism to generate a fused feature map. The feature representation generated by this method integrates spatial details and frequency structure information, exhibiting stronger discriminative power and robustness to disturbances such as scale and deformation. Furthermore, leveraging the efficient computational characteristics of its backbone network, it can quickly complete feature extraction with lower resource overhead, thereby providing higher-quality and more efficient feature input for downstream recognition tasks.

Embodiments of the present disclosure provide a system, method, and computer-readable medium with instructions for identifying the gender of a chick. The method includes moving the chick along a path associated with a stimulus means for inducing an open posture by the chick. The method further includes acquiring one or more images of the chick in an open posture, identifying one or more gender-associated features of the chick based at least in part on the one or more images, and determining the gender of the chick based at least in part on the one or more gender-associated features. One or more portions of the method may include any of a variety of machine learning techniques, such as supervised machine learning and / or unsupervised machine learning. For example, a supervised machine learning approach may be used to train a neural network to identify the pose of the chick, identify gender-associated features related to the chick's wings, and / or evaluate the gender-associated features to make a gender determination.

This invention belongs to the field of image processing technology and discloses a remote digital image analysis collaborative system. It includes: a virtual diagnosis module: acquiring continuous pathological slide sequences and performing spatial registration to obtain registered slides; a model building module: performing three-dimensional voxel reconstruction on the registered slides to obtain a three-dimensional voxel reconstruction model, followed by semantic enhancement to obtain a three-dimensional pathological voxel model; a collaborative interaction module: generating G virtual avatars of experts based on VR technology, annotating the three-dimensional pathological voxel model, and obtaining spatial anchor point annotation data for the experts; a graph-driven module: constructing a structured semantic tree based on the spatial anchor point annotation data, detecting annotation conflicts, and obtaining annotation conflict detection results; and a conflict resolution module: resolving conflicts in the annotation conflict detection results to obtain consensus suggestions. This invention improves the collaborative efficiency and reliability of conclusions in remote diagnosis, providing a systematic solution for the accurate diagnosis of complex pathological cases.

Techniques for scanning physical media on physical items and providing information about those physical items are provided. In one technique, a digital image that is generated by a mobile device and that indicates a list of ingredients in an item is identified. Text that contains the list of ingredients is identified within the digital image. It is determined whether a particular ingredient in the list of ingredients satisfies one or more criteria. In response to determining that the particular ingredient satisfies the one or more criteria, the digital image is modified by causing a portion, of the text within the digital image, that corresponds to the particular ingredient, to be highlighted while the digital image is displayed on a screen of the mobile device. In a related technique, the mobile device performs all the steps, whereas in another technique, a remote server performs one or more of the steps.

The application provides a coarse-grained aggregate mechanical behavior continuous-discontinuous numerical calculation method, including: establishing a numerical model of coarse-grained aggregate, the numerical model including a constant strain elastic triangular element and an initial thicknessless cohesive force element distributed along the boundary of the triangular element; determining the constitutive relation of the cohesive force element in the numerical model under a continuous deformation analysis framework; determining the contact relation between discrete triangular elements in the numerical model under a discontinuous deformation analysis framework; obtaining a continuous-discontinuous coupling model of the coarse-grained aggregate based on the determined constitutive relation and contact relation, inputting boundary constraint conditions and external loads into the continuous-discontinuous coupling model according to actual working conditions, and performing simulation calculation to obtain the mechanical properties and deformation failure forms of the coarse-grained aggregate under external loads. The application establishes a corresponding numerical model through digital image analysis and recognition technology, completes continuous-discontinuous coupling calculation of the mechanical behavior of coarse-grained aggregate, and takes into account solving accuracy and calculation efficiency.

This invention discloses a multi-gene mutation prediction method based on a combination of multi-task and multi-instance learning. Belonging to the fields of digital image analysis, pathology, and machine learning, the specific steps are as follows: Preprocessing existing pathological image data by staining normalization; constructing a feature matrix for each pathological image, and further using a two-layer multi-instance learning method to construct a package for each pathological image; constructing a multi-task deep learning network based on transformer and MobileNet; applying the model to a test set and outputting pathological image analysis results. This invention employs a multi-task deep neural network and applies it to the task of predicting multiple gene mutations based on pathological images. Compared to traditional single-task networks, this invention can simultaneously predict the results of multiple tasks, saving computational resources while improving accuracy; furthermore, combining the transformer module with traditional convolution considers both local and global features.

The invention relates to the technical field of medical detection, in particular to an antibody combination for detecting spermatogenic cells, a kit and application of the antibody combination. The antibody combination comprises an antibody of a zinc finger transcription factor 4, an antibody of a conjugation complex protein 3 and an antibody of zona pellucida binding protein. Specific recognition and semi-quantitative analysis of spermatogenic cells of all levels in samples are realized through standardized pretreatment, full-automatic immunohistochemical staining and digital image analysis for different types of samples; the method breaks through the technical bottlenecks that the traditional HE staining or Wright-Giemsa staining method is strong in subjectivity, difficult to distinguish cells with similar forms and greatly influenced by cell states and staining effects, and provides an efficient detection means for accurate pathological typing, spermatogenic function evaluation and dynamic curative effect monitoring of male infertility.

The present disclosure relates at least to the inspection of straws. A method and an arrangement for inspecting a straw are disclosed, involving the use of the straw as a light guide for inspecting the side wall of the straw based on light leakage of guided light emitted from the straw via the side wall, such as by way of damage in the side wall. It illuminates a first portion of the straw by means of one or more light sources, such that at least some of the light on the first portion is transmitted through the side wall of the straw into the straw and guided therein. One or more digital images are provided of another, second portion of the straw during said illumination. A light pattern captured by the one or more digital images is analysed, which corresponds to light escape of internally reflected light emitted from the second portion of the straw via the side wall of the straw. Damage can be detected as local spots of image data differences.

The system according to this embodiment aims to efficiently identify areas for improvement in digital illustrations and support the user in improving their drawing skills. [Solution] The system according to this embodiment comprises a reception unit, an analysis unit, a suggestion unit, and a provision unit. The reception unit receives the user's digital illustration. The analysis unit analyzes the digital illustration received by the reception unit. The suggestion unit suggests areas for improvement in the illustration based on the results of the analysis by the analysis unit. The provision unit provides the user with the areas for improvement suggested by the suggestion unit.

The application provides a corn ear phenotype acquisition method and device, and belongs to the technical field of image processing, and comprises the following steps: acquiring all edge pixel points of a cross-sectional image of a target ear; determining an angle value of each edge pixel point based on a preset pixel number, wherein the preset pixel number is determined based on a pixel size of the cross-sectional image; generating an ear row connection point of the target ear based on all the angle values, so as to determine an ear row phenotype index of the target ear. The corn ear phenotype acquisition method and device can quickly and automatically extract the ear row number phenotype index of the ear by analyzing and processing a digital image of the cross-sectional surface of the ear, calculating the data of the concave points on the edge of the cross-sectional image of the ear, and greatly reducing the demand for computing resources, improving the real-time performance of the calculation, and realizing online real-time measurement, so that the accuracy of the data can be quickly checked during measurement.

This invention relates to the field of nondestructive testing technology for low-carbon steel, specifically disclosing a thermo-sensitive dual-sensitivity composite coating, its preparation method, and its application. The thermo-sensitive dual-sensitivity composite coating comprises a stress-sensitive fluorescent layer and a thermochromic layer. The stress-sensitive fluorescent layer uses core-shell hybrid particles with mechanoluminescence enhancement as key functional fillers, while the thermochromic layer uses an irreversible thermochromic material based on IPN as the core functional material. This invention uses novel self-made functional materials to prepare the stress-sensitive fluorescent layer and thermochromic layer, enabling the thermo-sensitive dual-sensitivity composite coating to possess high-sensitivity signal sensing, optical enhancement, and permanent recording functions. Coupled with load excitation and digital image analysis processes, it transforms the stress-temperature coupled field information excited by deep defects under load into a high-intensity, highly interference-resistant, and permanently recordable visual signal, achieving precise location, quantification, and classification of defects.

Computer-implemented digital image analysis methods, apparatuses, and systems for robotic installation of surgical implants are disclosed. A disclosed apparatus plans a route within an anatomy of a patient from an incision site to a surgical implant site for robotic installation of a surgical implant. The apparatus uses digital imaging data to identify less-invasive installation paths and determine the dimensions of the surgical implant components being used. The apparatus segments the surgical implant into surgical implant subcomponents and modifies the surgical implant subcomponents, such that they can be inserted using the identified less-invasive installation paths.

The invention discloses a gastric cancer pathological tissue biopsy digital image analysis method, and relates to the field of image segmentation. The method mainly comprises the following steps: acquiring a pathological grayscale image; determining a first evaluation index according to the distribution deviation of the gray values in the connected domain; determining a second evaluation index according to the local saliency features at the pixel points in the connected domain and the overall gray level gradient trend; performing segmentation based on a comprehensive judgment index determined by the first evaluation index and the second evaluation index to obtain a region of interest; sequentially screening out a first type of regions and a second type of regions from all the regions of interest; dividing the second type of region into a low differentiation cell region and a suspected high differentiation cell region according to the area of the second type of region; and based on the local density of the pixel points in the suspected highly-differentiated cell region, segmenting the highly-differentiated cell region. According to the invention, region segmentation is carried out according to the wettability growth and shape features of the lesion region in the pathological grayscale image, and the segmentation precision of the pathological grayscale image is improved.

The application provides a kind of digital image correlation strain measurement system and method based on super lens, comprising: super lens, digital camera, illumination light source and computer;The super lens contains a plurality of super lens units, the light scattered or emitted by object is imaged, and the image formed is located in the plane where the digital camera photosensitive chip is located;The digital camera is used to collect the image of the measured object formed by the super lens;The computer is used to process the calibration and experimental image data collected by the digital camera, calculate the camera parameters through the calibration image, perform three-dimensional digital image analysis and calculation on the experimental image, and obtain the three-dimensional topography, displacement and deformation data of the measured object;The application can realize 3D-DIC measurement by single shooting of one camera, uses super lens to replace traditional lens, so that it can obtain simpler and more compact optical structure under the premise of maintaining imaging quality, and has the characteristics of high efficiency and no camera synchronization.

This invention relates to the field of image processing technology and discloses a method for inspecting the stamping quality of stamped parts. The method includes acquiring a digital image of the stamped part's surface, analyzing the surface curvature and material thickness gradient, and generating a spatial prior weight map; calculating the structural tensor of each pixel to determine the orientation and axial length ratio of the elliptical sampling neighborhood; sampling pixels along the elliptical sampling neighborhood to obtain an initial ternary pattern code; constructing a global feature histogram, accumulating contribution values ​​to statistical units, where the contribution value is the corresponding weight value of the pixel in the spatial prior weight map; concatenating the global feature histograms to generate a concatenated feature vector; and inputting the concatenated feature vector into a support vector machine classification model to determine whether the stamped part is qualified. This invention introduces a spatial prior weight map, integrating prior knowledge of the stamping process into the feature extraction process, allowing the detection focus to be on high-defect areas, making the extracted features more targeted and improving the accuracy of the detection.

A mobile radiography system has an x-ray source assembly configured to activate a digital x-ray detector through X-rays striking the digital x-ray detector and one or more shutters installed in a collimator in a stream of the X-rays configured to project an alignment image onto the digital x-ray detector. Further, the mobile radiography system has a processor that receives data indicative of the alignment image and the anatomy of interest, generates a first digital image indicative of the alignment image and the anatomy of interest, and analyzes the first image and determining if a focal spot of the x-ray source assembly is aligned with a focal axis of an anti-scatter grid and the digital x-ray detector based on the first digital image.

The invention discloses a hydraulic concrete bed load abrasion simulation device, which relates to the technical field of hydraulic structure safety assessment, and comprises the following steps: simulating real river water flow by adjusting the gradient of a bottom plate, the flow velocity, bed load particles and the like, and reproducing the concrete abrasion damage process. Aiming at the problems that an existing evaluation index is difficult to quantify a punching and grinding process, and response association between damage evolution and multiple indexes is not established, multi-parameter dynamic monitoring and intelligent analysis evaluation of punching and grinding behaviors are realized by integrating a mobile laser ranging system, an ultrasonic nondestructive monitoring device, a digital image analysis technology, a weighing sensing device and the like. The feedback optimization engineering design standard is realized, the hydraulic concrete abrasion protection strategy is formulated, and the accurate prediction of the service life of the structure is realized.