17907 results about "Image sensor" patented technology

A method for terrain and constraint planning a step plan includes receiving, at data processing hardware of a robot, image data of an environment about the robot from at least one image sensor. The robot includes a body and legs. The method also includes generating, by the data processing hardware, a body-obstacle map, a ground height map, and a step-obstacle map based on the image data and generating, by the data processing hardware, a body path for movement of the body of the robot while maneuvering in the environment based on the body-obstacle map. The method also includes generating, by the data processing hardware, a step path for the legs of the robot while maneuvering in the environment based on the body path, the body-obstacle map, the ground height map, and the step-obstacle map.

The invention relates to an intelligent industrial equipment state monitoring device and method, and the method comprises the steps: installing a vibration sensor, an acoustic sensor and an image sensor at key parts of industrial equipment, and comprehensively collecting the operation data of the equipment. In the data preprocessing stage, vibration and acoustic signals are filtered and denoised, and image data are denoised and enhanced. Extracting multi-dimensional characteristic parameters from three aspects of vibration, acoustics and images; a random forest algorithm is adopted for model training, and the method comprises the steps of data preparation, segmentation, decision tree construction, voting mechanism, majority voting, model verification and optimization, testing and the like. In the model identification stage, the real-time features are input into the trained model, and the equipment state is determined through decision tree prediction and voting summarization. And when an abnormal state is detected, setting a multi-level alarm response according to the probability, and generating a maintenance suggestion. According to the method, the whole-process intelligent monitoring of the industrial equipment is realized, and the fault identification accuracy and the maintenance efficiency are improved.

Systems and techniques are described for performing foveated sensing. In some aspects, a method (e.g., implemented by an image sensor) can include capturing sensor data for a frame associated with a scene, obtaining information corresponding to a region of interest (ROI) associated with the scene, generating a first portion (having a first resolution) of the frame corresponding to the ROI, generating a second portion of the frame having a second resolution, and outputting (e.g., to an image signal processor (ISP)) the first portion and the second portion. In some aspects, a method (e.g., implemented by an ISP) can receive, from an image sensor, sensor data for a frame associated with a scene, generating a first version (having a first resolution) of the frame based on an ROI associated with the scene, and generating a second version of the frame having a second resolution (lower than the first resolution).

An image sensor, a level shifter circuit, and an operation method thereof are provided. The image sensor includes a pixel circuit and a pixel driving circuit. The pixel driving circuit includes first, second, third, fourth, fifth, and sixth transistors. A first terminal of the first transistor is coupled to a first voltage. A first terminal of the second transistor is coupled to the first voltage, and a control terminal of the second transistor is coupled to a control terminal of the first transistor and a second terminal of the first transistor. A first terminal of the third transistor is coupled to the second terminal of the first transistor, and a second terminal of the third transistor is coupled to a ground voltage. A first terminal of the fourth transistor is coupled to a second terminal of the second transistor and an output terminal.

Ablation systems and methods of the present disclosure include a catheter including one or more image sensors. The one or more image sensors can facilitate, for example, positioning an ablation electrode at a treatment site of an anatomic structure and, additionally or alternatively, can facilitate controlling delivery of therapeutic energy to a treatment site of an anatomic structure.

In various examples, systems and methods for pose detection model training for predicting three-dimensional pose estimates using two-dimensional image data are provided. The occupant pose detection model may be trained using multi-view image sensor training data that includes image frames that capture a pose of a training subject within a machine interior using multiple synchronized optical image sensors placed around the machine interior that produce a set of captured image frames of the training subject from different viewpoints. Based on the multi-view image sensor training data, the occupant pose detection model may generate a set of individual, predicted 3D pose estimates for the training subject from a captured image frame from each of the respective optical image sensors. To adjust the occupant pose detection model during training, a loss feedback may be generated that comprises a pose alignment loss, a pose depth loss, and / or a ground truth kinematic loss.

The invention relates to a backside illuminated image sensor and a preparation method thereof, and electronic equipment, and relates to the technical field of integrated circuits, the backside illuminated image sensor comprises a substrate, and photodiodes and laminated isolation structures which are located on the substrate, are alternately arranged along a first direction parallel to the surface of the substrate, and extend along the direction towards the substrate. The photodiode comprises an isolation layer, a first photosensitive layer, a second photosensitive layer and a third photosensitive layer which are sequentially stacked in the direction away from the substrate. The first photosensitive layer internally comprises a plurality of first SiP layers arranged at intervals in the first direction, and the first SiP layers penetrate through the first photosensitive layer in the second direction and extend to the isolation layer. And the third photosensitive layer internally comprises a plurality of second SiP layers which are arranged at intervals along the first direction, and the plurality of second SiP layers penetrate through the third photosensitive layer along the second direction and extend to the second photosensitive layer, so that the number of photon-generated carriers can be increased, and the quantum efficiency of the device can be improved.

The invention relates to a backside illuminated image sensor, a preparation method thereof and electronic equipment. The backside illuminated image sensor comprises a substrate, a grating, photodiodes and target isolation structures, wherein the photodiodes and the target isolation structures are located on the first surface of the substrate, are alternately arranged in the first direction parallel to the first surface and extend towards the substrate; the substrate internally comprises a plurality of trench isolation structures which extend into the substrate through the first surface and are arranged at intervals in the first direction; the trench isolation structures and the target isolation structures over the trench isolation structures are arranged in a one-to-one manner; the photodiode comprises a SiAs laminated layer and a SiAs cover layer which are arranged along a direction away from the substrate, and a SiP layer which penetrates through the SiAs laminated layer along a first direction and a direction towards the substrate; the target isolation structure comprises a protruding part higher than the top surface of the photodiode; the grating and the protruding parts are prepared in the same process step at the same period. Signal crosstalk of the BSI image sensor and unnecessary damage caused by IMP can be avoided, and photoelectric conversion efficiency can be improved.

In various examples, image-based three-dimensional occupant assessment for in-cabin monitoring systems and applications are provided. An evaluation function may determine a 3D representation of an occupant of a machine by evaluating sensor data comprising an image frame from an optical image sensor. The 3D representation may comprise at least one characteristic representative of a size of the occupant, (e.g., a 3D pose and / or 3D shape), which may be used to derive other characteristics such as, but not limited to weight, height, and / or age. A first processing path may generate a representation of one or more features corresponding to at least a portion of the occupant based on optical image data, and a second processing path may determine a depth corresponding to the one or more features based on depth data derived from the optical image data and ground truth depth data corresponding to the interior of the machine.

A multispectral light field imaging system includes a primary lens, a microlens array, a first relay lens, a dichroic lens, a second relay lens, a third relay lens, a first image sensor, a first filter, a second image sensor and a second filter, wherein the microlens array is located at an image plane of the primary lens; the first relay lens together with the second relay lens and the third relay lens forms a 1:1 relay lens group imaging system on a spectral band 1 light path and a spectral band 2 light path respectively; the dichroic lens forms an included angle of 45° with a light axis; the first image sensor is located at a focal plane of the second relay lens, and the second image sensor is located at a focal plane of the third relay lens.

The invention relates to a backside illuminated image sensor and a preparation method thereof, and electronic equipment, and relates to the technical field of integrated circuits, the backside illuminated image sensor comprises a substrate, and photodiodes and laminated target isolation structures which are located on a first surface of the substrate, are alternately arranged along a first direction parallel to the first surface, and extend towards the substrate; the substrate internally comprises a plurality of trench isolation structures which extend into the substrate through the first surface and are arranged at intervals in the first direction; the trench isolation structures and the laminated target isolation structures right above the trench isolation structures are arranged in a one-to-one manner; the laminated target isolation structure comprises isolation parts and insulation parts which are sequentially and alternately laminated along a second direction deviating from the substrate; the photodiode comprises at least two photosensitive layers which are sequentially stacked in the second direction, the longitudinal sections of the photosensitive layers are T-shaped, one photosensitive layer makes contact with the first surface of the substrate, substrate damage caused by ion implantation can be avoided, and meanwhile the photoelectric conversion efficiency and the quantum efficiency are improved.

The invention relates to a backside illuminated image sensor and a preparation method thereof, and an electronic device, and relates to the technical field of integrated circuits, and the method comprises the steps: providing a substrate which comprises an isolation layer and a plurality of first isolation structures which are arranged at intervals in a first direction parallel to the surface of the substrate; forming first isolation parts in the substrate, wherein the first isolation parts and the first isolation structures are arranged in a one-to-one manner and extend to the isolation layer through the back surface of the substrate; removing the substrate between the adjacent first isolation parts to obtain side wall semiconductor layers located on the side surfaces of the first isolation parts and first grooves between the adjacent side wall semiconductor layers; the size of the side wall semiconductor layer is gradually increased in the direction close to the isolation layer. And forming a bottom photosensitive layer in the first groove, and epitaxially growing a top photosensitive layer on the bottom photosensitive layer. And forming a second isolation part connected with the first isolation part in a gap between the adjacent top photosensitive layers, thereby improving the photoelectric conversion efficiency and the quantum efficiency.

The present disclosure relates to a system to proactively detect in real time one or more threats in crowded areas. The present disclosure presents a proactive system for real-time threat detection in crowded areas. Utilizing a network of imaging sensors and advanced machine learning algorithms, the system identifies suspicious individuals, objects, and behavioral patterns within a predefined area. The system detects potential threats such as individuals on watch lists, suspicious objects like unattended bags, and abnormal behaviors indicative of security risks, by continuously monitoring and analyzing images and video feeds. Upon detection, the system promptly notifies authorities, providing detailed information on threat location, suspected individuals, and behavioral analysis. Privacy-preserving measures, including encryption of facial recognition data, ensure compliance with privacy regulations. The present disclosure offers a scalable, efficient, and automated solution to enhance security measures, reduce response times, and safeguard public safety in dynamic urban environments.

Self-leveling inspection system methods and devices for use in inspecting buried pipes or other cavities are disclosed. The system includes a camera head with an image sensor, an orientation sensor, and a signal processing module including a processing programmed to receive an image from the image sensor, and an orientation signal from the orientation sensor, generate a second image based at least in part on information provided from the orientation sensor, and store the second image in a non-transitory memory.

The invention relates to a backside illuminated image sensor preparation method and a backside illuminated image sensor, and relates to the technical field of integrated circuits, the backside illuminated image sensor preparation method comprises the following steps: providing a substrate comprising a first top surface, the first top surface comprising an isolation layer and an initial semiconductor layer stacked in sequence along a first direction deviating from the first top surface; forming a plurality of isolation lamination layers which are arranged at intervals along a second direction on the top surface of the initial semiconductor layer, and sequentially forming a first semiconductor layer and a second semiconductor layer which are laminated and contain different pentavalent elements between adjacent isolation lamination layers; diffusing a first pentavalent element of the first semiconductor layer to the initial semiconductor layer to obtain a first target semiconductor layer; diffusing a second pentavalent element of the second semiconductor layer to the first semiconductor layer to obtain a second target semiconductor layer; and a dielectric layer covering the top surface of the second semiconductor layer and the exposed outer surface of the isolation lamination layer is formed, so that the electron concentration of the photosensitive area is increased, and the photosensitive performance of the BSI image sensor is improved.

A monolithic image sensor (200) comprising: a pixel area (210, 220) sensitive to electromagnetic irradiation and comprising a first pixel area (210) comprising an array of synchronous first image sensor pixels (211) and further comprising a second pixel area (220) comprising hybrid second image sensor pixels (221, 222), a change detector area (230) comprising multiple asynchronous change detectors (231, 232), and a synchronous intensity read-out circuitry (260). A first photoreceptor (215) of a respective first image sensor pixel (211) is electrically coupled to the synchronous intensity read-out circuitry (260). A second photoreceptor (225) of a respective hybrid second image sensor pixel (221, 222) is electrically coupled to the synchronous intensity read-out circuitry (260) with a first connection (241) and electrically coupled to a respective asynchronous change detector (231, 232) out of the multiple asynchronous change detectors (231, 232) with a second connection (242). The change detector area (230) is a distinct part of the image sensor 200 which is separate from the pixel area (201).

A system, method, and computer program product for generating a digital image is disclosed. In use, a first image and a second image are received from a first image sensor, where the first image sensor detects wavelengths of a visible spectrum. A third image and a fourth image are received from a second image sensor, where the second image sensor detects wavelengths of a non-visible spectrum. Using an image processing subsystem, a resulting image is generated by combining one of the first image or the second image, with one of the third image or the fourth image.

The invention relates to a multidirectional machine vision detection system and method for automobile parts, and the system comprises an image sensor module, a self-adaptive light source control module, a mechanical arm system, and a data transmission and analysis module. The self-adaptive light source control module adjusts the intensity and angle of a light source in real time according to the detection environment and the gloss characteristic of the surface of the accessory, interference of reflection and shadow is reduced, the mechanical arm system drives the accessory to move at multiple angles through an inverse kinematics algorithm, and it is ensured that the surface of the accessory is fully covered; and the data transmission and analysis module is used for processing the collected image data, identifying potential defects of the accessories through a deep learning algorithm and a high-dimensional feature analysis technology, and generating a detection report. The method is suitable for quality detection of automobile parts with complex shapes and high glossiness.

The invention relates to an aerial photography target detection method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring an aerial image acquired by an image sensor; inputting the aerial image into a pre-trained target detection model to obtain a target detection result; the target detection model comprises a backbone network, a neck network and a head network; wherein the backbone network is used for performing feature extraction on an aerial image to obtain image extraction features; the neck network is used for performing multi-scale fusion on the image extraction features to obtain a plurality of fusion features of different scales; the neck network comprises a bidirectional information transfer network, the bidirectional information transfer network comprises a separation and attention enhancement module, and the separation and attention enhancement module is used for generating fusion features corresponding to tiny targets; and the head network comprises a detection head corresponding to the tiny target and is used for obtaining a target detection result corresponding to the fusion feature based on the fusion feature. By adopting the method, the detection accuracy under the complex aerial image can be improved.

The invention relates to the field of image enhancement, in particular to an image enhancement method and system of a vehicle-mounted image sensor. The method comprises the following steps: acquiring driving record images of a vehicle at multiple angles; dynamic scene self-adaptive exposure adjustment is carried out on the driving record images of the vehicle at the multiple angles, so that multiple self-adaptive exposure driving images are obtained; carrying out deep network noise identification on the plurality of adaptive exposure driving images, and carrying out dynamic filtering and noise reduction on sub-images one by one so as to generate a plurality of filtering and noise reduction optimized images; carrying out image texture analysis on the plurality of exposure sub-images, and carrying out texture distortion reconstruction to construct a plurality of texture reconstruction images; and road object visual identification is carried out on the plurality of texture reconstruction images, and adaptive contrast enhancement processing is carried out, so that a plurality of detail contrast enhancement images are constructed. According to the invention, a high-definition and stable panoramic vehicle-mounted image is realized.

The invention provides a neuromorphic visual target tracking method and system based on image processing, and relates to the technical field of neuromorphic calculation, and the method comprises the steps: fusing the input of an event camera and a conventional image sensor, constructing a combined input tensor, and introducing a multi-scale convolution and synaptic event driving mechanism. Quick response and stable feature extraction of a high-speed moving target are realized, and coding block mistaken deletion and tracking loss caused by quick movement of the target are effectively avoided, so that system delay is reduced. Meanwhile, in combination with significance entropy difference evaluation and a dynamic brightness enhancement mechanism, the target judgment accuracy under low illumination and complex backgrounds is improved; redundant noise blocks are screened out through a significance weight function and confidence calculation, the redundancy calculation burden is relieved, and the lightweight characteristic of the system is guaranteed. A memory trajectory tensor and dynamic template adjustment mechanism based on a recurrent neural network is further introduced, time sequence consistency verification and self-adaptive updating are achieved, and the stability and robustness of the tracking process are enhanced.

The invention relates to the technical field of phytotron control systems, in particular to a seed seedling phytotron control system and a control method thereof, which integrate multi-dimensional environment perception, intelligent analysis and decision, precise environment regulation and control, a central controller and a data storage and analysis platform. A seedling raising environment is monitored in real time through temperature and humidity, illumination, CO2 concentration, soil moisture and an image sensor, an intelligent analysis decision module preprocesses data, establishes a growth model, generates a control strategy and optimizes a target by using an advanced algorithm, and an accurate environment regulation and control module executes the strategy and regulates temperature, humidity, illumination and the like. The central controller coordinates operation of the modules and realizes man-machine interaction, and the data storage and analysis platform is responsible for storing data and supporting cloud analysis so as to realize efficient seedling culture management and significantly improve the seed emergence rate from 75% of a traditional method to 92%, and greatly reduce seed waste.

The invention discloses a self-isolation type image sensing structure, a sensor and a preparation method, and belongs to the field of semiconductors, the self-isolation type image sensing structure is characterized in that a shallow trench isolation structure is exposed after the back surface of a substrate is thinned, then a first semiconductor layer is extended on the back surface of the substrate, and a first isolation structure is prepared in the first semiconductor layer; sequentially depositing a second semiconductor material layer and a metal grating material layer on the first semiconductor layer; sequentially etching the metal grating material layer and the second semiconductor material layer to form a plurality of metal grating structures distributed at intervals and corresponding self-isolation structures; extending a plurality of photosensitive layers in the photosensitive region groove between the adjacent self-isolation structures to form a photosensitive region; and then activating, preparing a filter layer and the like are carried out to obtain a complete back-illuminated image sensor. The self-isolation photodiode is obtained by changing the structural distribution of the photodiode, unexpectedly, the problem that the substrate is damaged by doping is solved, meanwhile, the crosstalk effect is greatly reduced, and the performance of the image sensor is improved.

The invention discloses a valve support quality detection method based on image recognition, and particularly relates to the technical field of valve support quality detection.The method comprises the steps that real-time temperature data and image data in the valve support quality detection process are acquired; outputting a temperature-image relation model through joint calibration of a temperature sensor and an image sensor; compensating the image data of the valve bracket based on the real-time temperature data and the temperature-image relation model; building an initial defect identification model, adjusting model parameters based on the real-time temperature data and the preliminarily compensated image, using a time sequence causal relationship model to predict image quality degradation, adjusting the model parameters in advance, and outputting a trained defect identification model; controlling a receptive field and a feature fusion coefficient of the defect identification model; the feature fusion coefficient is used for adjusting the feature fusion weight of each scale; and the training priority is managed by using clustering analysis, and the detection precision of the temperature anomaly region is optimized.

The embodiment of the invention provides a semiconductor structure, a manufacturing method of the semiconductor structure and an image sensor, and relates to the technical field of semiconductor manufacturing. The semiconductor structure comprises a substrate and a photoelectric function layer formed on the surface of the substrate, the photoelectric function layer comprises a photoelectric sensing layer and an isolation structure used for dividing the photoelectric sensing layer into a plurality of photoelectric sensing areas; the photoelectric sensing area comprises a plurality of photoelectric sensing material layers which are arranged in a stacked mode and a cross-layer doping structure which extends in the normal direction of the photoelectric sensing layers. The doping type of the cross-layer doping structure is the same as that of the photoelectric sensing layer; wherein the cross-layer doping structure is formed through an ion implantation process; the normal direction of the photoelectric sensing layer is taken as the depth direction of ion implantation and the thickness direction of the photoelectric sensing material layer, and the ion implantation depth of the cross-layer doped structure is at least greater than the thickness of the photoelectric sensing material layer farthest from the substrate along the normal direction of the photoelectric sensing layer. According to the embodiment of the invention, the imaging quality of the image sensor is improved.

A device may include a tip tilt camera module and a dynamic flexible printed circuit structure. The camera module as a whole may tilt around one or more axes. Within the camera module, the camera module may include one or more lenses and an image sensor, whereby the relative position between the lenses and image sensor may be adjustable. The printed circuit structure may provide an electrical connection between the camera module and one or more other components of the device outside the camera module. The printed circuit structure may include one or more flexible portions, at least one portion of which may be placed in torsion during rotation of the camera module.

The invention relates to the technical field of machine vision structure health monitoring, and discloses a steel structure weld fatigue cracking real-time monitoring system based on machine vision. The system comprises a space-time registration and fusion module, a multi-scale feature analysis module, a health monitoring module, a crack deduction calculation module and a regulation and control strategy generation module. Performing space-time registration and pixel-level fusion through the visual data of the plurality of image sensors to generate a synchronous multi-source image stream; a multi-level welding seam characteristic spectrum is constructed through multi-scale characteristic analysis, and a welding seam structure knowledge base is dynamically updated; the knowledge base and the real-time characteristic spectrum are used for monitoring the welding seam health state, and abnormity is recognized; deducing a crack initiation position and an evolution path in combination with historical damage data; and real-time load information is fused to pre-estimate the remaining service life, and a structural integrity regulation and control strategy is generated online. According to the invention, high-precision fusion of the multi-source visual data and active prediction of the crack trend are realized, and the monitoring accuracy and the early warning capability are improved.

The invention provides a pixel signal output circuit and an image sensor, and the circuit comprises a pixel module which is used for generating a pixel signal; and the feedback capacitance module is connected with the output end of the pixel module and is used for equivalently reducing the total load capacitance of the pixel module so as to accelerate the establishment of a pixel signal. The feedback capacitor module is additionally arranged at the output end of the pixel module, and the total load capacitance of the pixel module is equivalently reduced by utilizing the capacitance of the feedback capacitor module, so that the time constant of the pixel signal output circuit can be effectively reduced, the slew rate is increased, the establishment speed of the pixel signal is accelerated, and the pixel signal output efficiency is improved. The problem of how to improve the establishment speed of the pixel signal is solved.

A noise detecting playback system is provided to facilitate adaptive output of audio content by an audio player in response to detecting noise interferences such as external noise outside of the playback. The detection playback system assesses microphone signals and sensor data of the playback system for signs of attention requiring features to trigger playback of the audio content. Microphone signals may provide volume level of a particular external noise, which is contrasted with output volume of the audio content, other noises in the environment, and / or a lack of detected noise in the environment to determine that the particular external noise is interfering or potentially interfering with the audio content. Image sensor data of the surroundings of the listener acquired by a camera coupled to a personal listening device may also be assessed for attention features associated with an external noise.

The invention discloses a transformer fault intelligent detection method and device based on deep learning multi-mode fusion, computer equipment and a readable storage medium. The method comprises the steps that firstly, RGB image data of a target transformer are collected by means of an image sensor, infrared thermal imaging image data are collected by means of an infrared sensor, and sound signals are collected by means of a sound sensor; and preprocessing the data, taking the preprocessed data as multi-modal detection data, and inputting the multi-modal detection data into a pre-trained multi-modal fault recognition model which comprises a sensing layer, a fusion layer, a backbone network and an output layer which are cascaded in sequence, so as to obtain a fault detection result of the target transformer. According to the method, multi-modal data are fused, the deep learning advantage is exerted, the comprehensiveness and accuracy of transformer fault detection are improved, and an effective means is provided for intelligent operation and maintenance of a power system.