24 results about "Defined Imaging" patented technology

The invention discloses a high-performance video and UI (User Interface) display method based on a layered rendering architecture, which comprises the following steps of: defining image display layers and a priority sequence thereof, sequentially rendering each layer according to a sequence from low priority to high priority, and ensuring that the high priority layer can correctly cover the low priority layer; and controlling the display sequence of each layer by adopting a double-track system that a local display sequence is determined according to a z-index value in a lamination priority and the same priority, and synthesizing a final screen display image. The technical scheme of the invention has the main advantages that real-time rendering of a high-quality video stream is supported while UI responsiveness is kept, and the requirement of a high-performance scene is met; it is ensured that the UI layer is always kept above the video layer, or the stacking sequence is dynamically adjusted according to application requirements; and a hierarchical design principle is adopted, and loose coupling is realized among the modules, so that independent upgrading and maintenance are facilitated, and the expandability of the system is enhanced.

Surface determination systems, threat detection systems and medical treatment systems are described. According to one aspect, a surface determination system includes processing circuitry configured to access a three-dimensional complex-valued image volume of a target, define image locations of the image volume using first and second dimensions of the image volume, for each of the first locations, identify voxels along a third dimension of the image volume that correspond to the respective first location, for each of the first locations, select one voxel that corresponds to the first location as having an increased amplitude compared with other voxels that correspond to the first location, and for each selected voxel, use phase information to identify a second location in the third dimension for the selected voxel that corresponds to a location of a surface of the target and that is different than a third location of the respective voxel.

This invention discloses a navigation-following unmanned surface vessel (USV) formation control method based on active vision, comprising the following steps: constructing a kinematic model of the USV based on a geodetic coordinate system; establishing a gimbal monocular camera model for the gimbal camera mounted on the USV; defining servo tracking errors for the navigation-following USV formation system by combining the USV kinematic model and the gimbal monocular camera model; defining image coordinate errors based on the viewing angle constraints of the gimbal monocular camera; designing a motion controller and adaptive parameter update law for the USV using the Lyapunov synthesis method; and designing a gimbal camera steering controller and adaptive parameter update law using the Lyapunov synthesis method. This method ensures the smooth implementation of visual servo control of the USV by defining servo tracking errors and image coordinate errors, and then incorporating these two errors into the Lyapunov synthesis method to design the USV motion controller, the gimbal camera steering controller, and the adaptive parameter update law.

The invention provides a method for determining the organic matter surface porosity of the total area occupied by organic matter pores, which comprises the following steps: carrying out an electron microscope scanning experiment on a shale sample to obtain a first scanning electron microscope image of the shale sample; extracting all organic matter regions in the first scanning electron microscope image of the shale sample by using preset image processing software to obtain the total area fraction of organic matters on the surface of the shale sample; obtaining the average surface porosity of organic matter pores from the first scanning electron microscope image of the shale sample according to a preset fifth rule; and according to the total area fraction of the organic matters on the surface of the shale sample and the average surface porosity of the organic matter pores, obtaining the organic matter surface porosity of the organic matter pores in the total area according to a preset formula. The organic matter surface porosity of the organic matter pores in the total area can characterize the characteristics of the shale surrounding pore structure, reflect the shale organic matter thermal evolution process, and provide a basis for evaluating shale gas reservoir and dessert section optimization.

The application discloses an image classification method and device, a storage medium and a computer device. The method is applied to the computer device and comprises the following steps: in a self-defined image classification mode of an electronic album, in response to a triggering operation of a user on an update control of an image corresponding to a to-be-managed image category, updating the image in the to-be-managed image category, calling a training interface, obtaining a first image classification model corresponding to the self-defined image mode through the training interface, the model being pre-trained, and performing transfer training on all images of the to-be-managed image category according to the first image classification model, so as to obtain a first image classification model after transfer training. The classification of the updated image can be matched by using the first image classification model after transfer training, the classification accuracy is improved, finally, the to-be-classified images of the electronic album are classified by using the trained first image classification model, the image classification efficiency and accuracy are improved, and the image searching efficiency is further improved.

A head-mounted display system includes an emissive micro-display including an array of light emitters corresponding to pixels, where the array of light emitters is configured to output image light that defines images. The system also includes an aspheric lens configured to receive the image light from the emissive micro-display and correct the image light. The system also includes a first surface mirror configured to redirect the image light from the aspheric lens from a first direction to a second direction substantially orthogonal to the first direction. Moreover, the system includes a collimating optic configured to receive the image light from the first surface mirror and collimate the image light. In addition, the system includes an eyepiece configured to receive the image light from the collimating optic and to direct the image light to an eye of a user.

The decoding device includes circuitry and a memory connected to the circuitry. The circuitry acquires an image from a bitstream and a first parameter associated with the image. The first parameter includes modal information representing the image category, which indicates that the image category is at least one of the following: a visible light image, an infrared image, an ultraviolet image, an undefined image, or a pre-defined image category for extension.

A system (100), and method (200) thereof, is provided for identifying and forecasting animal activity. The method (200) may comprise receiving (202) the images (112) from the camera (110) to define image specific raw data (114); assimilating (204) the image specific raw data (114) with contemporaneous weather data (140); determining (206) a mean rate of animal sightings for each of a plurality of prior time intervals associated with the assimilated image specific raw data using a first analytics model; minimizing (208) a difference between observed sightings and predicted sightings based at least in part on outputs from the first analytics model using a second analytics model; and determining (212) an amount of likely animal sightings for each of a plurality of future time intervals based at least in part on the outputs from the first analytics model and outputs from the second analytics model using a third analytics model.

This application discloses an image retrieval method and apparatus, relating to the field of knowledge distillation technology. The method includes: using user-input query text as the retrieval source, and employing text semantic understanding and image feature matching algorithms to filter and output target images from a pre-defined image library that match the text content description, thereby completing cross-modal text-image retrieval. This solves the technical problems in related technologies, such as the difficulty in deeply mining core knowledge like fine-grained probability distribution and coarse-grained structural features of the attention mechanism during image retrieval, and the inability of the distillation process to cover all dimensions of knowledge at the attention level, resulting in insufficient integrity of knowledge transfer. The method achieves the technical effect of helping users quickly locate target images with concise text descriptions through deep correlation matching between text and images, effectively simplifying the image search operation process, and providing users with an efficient and convenient image retrieval and browsing experience.

Adaptive acquisition control timing control for image and video acquisition and processing includes obtaining, by an auto-exposure compensation component of an image processing pipeline of an image capture apparatus, during a current sensor readout window corresponding to obtaining current input image data from an image sensor of the image capture apparatus, in accordance with defined image acquisition and processing timing data, current auto-exposure compensation data for processing subsequent input image data obtained from the image sensor during a subsequent sensor readout window sequentially immediately subsequent to the current sensor readout window, and outputting, to a second data storage unit instance of the image processing pipeline, by the auto-exposure compensation component, during the current sensor readout window, the current auto-exposure compensation data.

The present application relates to a kind of training method, equipment and medium for the multi-task prediction model of medical image, the method includes the following steps: obtaining multi-center, multiple devices, multiple tracer initial medical image and clinical risk factor feature, the initial medical image includes PET image and CT image;First equalization processing is carried out to initial medical image corresponding lesion segmentation gold standard, obtain equalized 3D image sequence;Resampling is carried out to the 3D image sequence, extract deep learning feature and pre-defined image group feature;Second equalization processing is carried out to the deep learning feature, and feature post-processing is carried out to the equalized feature;The deep learning feature, pre-defined image group feature and clinical risk factor feature obtained are spliced, and final feature is obtained;With final feature as input, multi-task prediction model is trained and obtained.Compared with prior art, the present application has the advantages of high medical image processing accuracy, suitable for multi-modal image and the like.

A surgical system includes a handheld cable housing with a user input device positioned thereon. The surgical system includes an endoscope shaft with a distal end and a proximal end. The proximal end of the endoscope shaft is coupled to the handheld cable housing, where the distal end of the endoscope shaft comprises an image sensor. The endoscope shaft is rotatable relative to the handheld cable housing. One or more angular position sensors configured to measure an angular offset relative to a defined image horizon. Upon receiving angular offset data indicative of an angular offset relative to the defined image horizon, an image processor generates rotated image data based on the angular offset data and causes display of the rotated image data.

A method for classifying plants for agricultural purposes. The method includes: detecting a field section having plants using an optical detection unit inclined toward the field section to obtain image information having a rear image edge having an image width and a front image edge having a larger image width; classifying the plants in the image information into first and second plant classes using an algorithm to treat the plants of the second plant class with a liquid spray agent, in accordance with the classification. The step of classifying comprises a step of reclassifying, in which classified plants are reclassified from the second plant class to the first plant class using the algorithm if they extend in a rear image section of the image information defined by a defined image separation line from a lateral image edge of the image information maximally up to a defined reclassification boundary line.

The present application relates to the technical field of digital watermarking, and proposes a traceability watermarking method and system resistant to partial screen shooting. The watermarking generation method resistant to partial screen shooting comprises the following steps: converting watermark information into a watermark bit matrix; replacing 0 and 1 in the watermark bit matrix by defined image blocks and through Kronecker product, to obtain a watermark image matrix; periodically replacing a bit block without a bit in the watermark image matrix by a positioning block, to form a hybrid watermark matrix, and redundantly copying the hybrid watermark matrix to obtain a redundant watermark matrix; mapping the bit block to a red channel on a white background, rendering the positioning block to a green channel, keeping a blue channel white, and generating a visual watermark image with the ability to resist local shooting interference. W M x N WM WM t 0 、t 1 WM1 WM1 t m WM2 WM3 RGB t 0 、t 1 t m W rgb The present application can effectively deal with watermark extraction under the condition that screen content is not complete and lacks synchronization basis, and ensure high accuracy of watermark extraction.​​​​​​​​​​​​​

The invention discloses an industrial quality inspection confrontation attack defense method and device, electronic equipment, a medium and a program product, and relates to solving the problem of how to effectively defend confrontation attacks at low cost. The anti-attack defense method for industrial quality inspection in the embodiment of the invention comprises the following steps: collecting image data of an industrial product through a visual sensor; defining the image attributes and features related to the defects of the industrial product or material as labels; performing machine learning by using a combination of the image data and the labels as training data, and constructing a quality inspection model for detecting and classifying defects of industrial products or materials; generating an adversarial sample by generating an adversarial network, generating a disturbance corresponding to the image data using the image data, and superimposing the disturbance on the image data; mixing the training data with the adversarial samples to generate an adversarial training set; and performing adversarial training on the quality inspection model by using the adversarial training set.

The invention discloses an image fusion enhancement method and system based on an FPGA. The method comprises the following steps: acquiring image data comprising a CLAHE enhanced image of a first channel and an original image of a second channel; performing two-dimensional mean filtering processing on the original image to generate a mean image; defining image blocks; calculating the offset position of the pixel in the image block to which the pixel belongs; calculating the distance from the pixel to the center of the image block to which the pixel belongs according to the offset position of the pixel in the image block to which the pixel belongs; loading and switching a weighting function curve by utilizing a programmable lookup table; obtaining a weight value according to the weight function curve and the distance from the pixel to the center of the image block to which the pixel belongs; and performing weighted fusion on the CLAHE enhanced image pixel value and the mean value image pixel value according to the weight value, and outputting a weighted fusion pixel value and an effective signal. According to the invention, flexible switching of image fusion strategies during operation can be realized, and the smoothness and adaptive ability of image enhancement are improved, so that the technical problem that a fixed fusion weight in a traditional hardware structure is not suitable for multiple scenes is solved.

The invention relates to the technical field of digital watermarking, and provides a traceability watermarking method and system capable of resisting partial screen shooting. The watermark generation method for resisting partial screen shooting comprises the following steps: converting watermark information W into an M * N watermark bit matrix WM; respectively replacing 0 and 1 in the watermark bit matrix WM with defined image blocks t0 and t1 through a Kronecker product to obtain a watermark image matrix WM1; in the watermark image matrix WM1, bit blocks without bits are periodically replaced with positioning blocks tm to form a mixed watermark matrix WM2, and the mixed watermark matrix WM2 is subjected to redundant copying to form a redundant watermark matrix WM3; and on a white RGB background, mapping the bit blocks t0 and t1 to a red channel, rendering the positioning block tm into a green channel, keeping the blue channel white, and generating a visual watermark image Wrgb with local shooting interference resistance. The method can effectively cope with watermark extraction under the conditions that shot or captured screen content is incomplete and synchronous basis is lacked, and ensures high accuracy of watermark extraction.

The embodiments relate to a method and a technical equipment for implementing the method. The method comprises receiving encoded omnidirectional video content for displaying, wherein the encoded omnidirectional video content comprises a viewport region, a margin region outside the viewport region and a background region (801); defining image regions to be included in the margin region, wherein the definition is based on a margin speed threshold (802); determining a head speed and a direction of motion (803); determining when the head speed is greater than or equal to the margin speed threshold, and as a response to the determining, adding negative margins in one or more direction with respect to the viewport (804); downloading the viewport with a first quality; and downloading the negative margins at a quality lower than the first quality (805).

The invention relates to an image generation device (161, 162, 163) of a vehicle (10) or for a vehicle (10), comprising: an input device (20) for inputting data defining an image (17); a digital projector (26) for projecting the defined image (17) onto or near a surface (18) of the vehicle (10); and an interface (30) for establishing communication between the input device (20) and the digital projector (26). The invention also relates to a vehicle (12) comprising such an image generation device (161, 162, 163) and to a method of generating an image using such an image generation device (161, 162, 163).

Adaptive acquisition control timing control for image and video acquisition and processing includes obtaining, by an auto-exposure compensation component of an image processing pipeline of an image capture apparatus, during a current sensor readout window corresponding to obtaining current input image data from an image sensor of the image capture apparatus, in accordance with defined image acquisition and processing timing data, current auto-exposure compensation data for processing subsequent input image data obtained from the image sensor during a subsequent sensor readout window sequentially immediately subsequent to the current sensor readout window, and outputting, to a second data storage unit instance of the image processing pipeline, by the auto-exposure compensation component, during the current sensor readout window, the current auto-exposure compensation data.

A system, and method thereof, is provided for identifying and forecasting animal activity. The method may comprise receiving the images from the camera to define image specific raw data; assimilating the image specific raw data with contemporaneous weather data; determining a mean rate of animal sightings for each of a plurality of prior time intervals associated with the assimilated image specific raw data using a first analytics model; minimizing a difference between observed sightings and predicted sightings based at least in part on outputs from the first analytics model using a second analytics model; receiving forecasted weather data for a plurality of future time intervals; and determining an amount of likely animal sightings for each of the plurality of future time intervals based at least in part on the outputs from the first analytics model and outputs from the second analytics model using a third analytics model.

A spray system comprising: a paint nozzle (110) configured to dispense paint onto a surface; an arm configured to move the paint nozzle over the surface according to an image scan pattern (310); a pressurization device operable to feed paint into a paint supply line, the paint supply line extending upwardly to the paint nozzle; and a controller arranged to control the pressurization equipment. The controller is configured with a control law comprising a feedback component for maintaining an output paint pressure of the paint supply line at a setpoint value, and further comprising a feed-forward component dependent on image data in a region (320) of the user-defined image (300), which region is to be then printed according to an image scan pattern.

The invention provides an interactive projection method, system and device and electronic equipment, and belongs to the technical field of vehicle-mounted interactive systems.The method comprises the steps that a user-defined image is obtained, and the image is collected and edited by a user through a client; performing transcoding and format adaptation on the image to enable the image to conform to the color and brightness characteristics of a projection light source, and generating a corresponding projection instruction; and transmitting the image subjected to transcoding and format adaptation and a corresponding projection instruction to a projection control unit for dynamic light and shadow projection. According to the method, a free drawing or picture uploading function is provided for a user through a vehicle machine or a mobile phone App, the picture is projected to the ground or the wall through a vehicle lamp, meanwhile, the user is allowed to add background music for each image, multimedia interaction for improving individuation, entertainment experience and picture and sound synchronization is provided for the user, and therefore a smooth and attractive audio-visual effect is created.

One or more systems, devices, computer program products and / or computer-implemented methods of use provided herein relate to generative artificial intelligence (AI)-based large-scale automated evaluation of autonomous planning software (APS) performance. For example, a system can comprise a memory that can store computer executable components and a processor that can execute the computer executable components stored in the memory. The computer executable components can comprise an image generation component that can generate one or more diagnostic images. The computer executable components can further comprise an image evaluation component that can generate, based on defined image criteria, respective auto-positioning image matching scores for respective diagnostic images of the one or more diagnostic images by comparing the respective diagnostic images with respective sets of template images.