9124 results about "Image analysis" patented technology

An adaptive strobe illumination control process for use in a digital image capture and processing system. In general, the process involves: (i) illuminating an object in the field of view (FOV) with several different pulses of strobe (i.e. stroboscopic) illumination over a pair of consecutive video image frames; (ii) detecting digital images of the illuminated object over these consecutive image frames; and (iii) decode processing the digital images in an effort to read a code symbol graphically encoded therein. In a first illustrative embodiment, upon failure to read a code symbol graphically encoded in one of the first and second images, these digital images are analyzed in real-time, and based on the results of this real-time image analysis, the exposure time (i.e. photonic integration time interval) is automatically adjusted during subsequent image frames (i.e. image acquisition cycles) according to the principles of the present disclosure. In a second illustrative embodiment, upon failure to read a code symbol graphically encoded in one of the first and second images, these digital images are analyzed in real-time, and based on the results of this real-time image analysis, the energy level of the strobe illumination is automatically adjusted during subsequent image frames (i.e. image acquisition cycles) according to the principles of the present disclosure.

Systems and methods may calibrate an indicator of speed of an autonomous vehicle. In one implementation, a system may include at least one processor programmed to: receive from a camera at least a plurality of images representative of an environment of the vehicle; analyze the plurality of images to identify at least two recognized landmarks; determine, based on known locations of the two recognized landmarks, a value indicative of a distance between the at least two recognized landmarks; determine, based on an output of at least one sensor associated with the autonomous vehicle, a measured distance between the at least two landmarks; determine a correction factor for the at least one sensor based on a comparison of the value indicative of the distance between the at least to recognized landmarks and the measured distance between the at least two landmarks.

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

Digitized image data are input into a processor where a detection component identifies the areas (objects) of particular interest in the image and, by segmentation, separates those objects from the background. A feature extraction component formulates numerical values relevant to the classification task from the segmented objects. Results of the preceding analysis steps are input into a trained learning machine classifier which produces an output which may consist of an index discriminating between two possible diagnoses, or some other output in the desired output format. In one embodiment, digitized image data are input into a plurality of subsystems, each subsystem having one or more support vector machines. Pre-processing may include the use of known transformations which facilitate extraction of the useful data. Each subsystem analyzes the data relevant to a different feature or characteristic found within the image. Once each subsystem completes its analysis and classification, the output for all subsystems is input into an overall support vector machine analyzer which combines the data to make a diagnosis, decision or other action which utilizes the knowledge obtained from the image.

Game interface tracks the position of one or more game controllers in 3-dimensional space using hybrid video capture and ultrasonic tracking system. The captured video information is used to identify a horizontal and vertical position for each controller within a capture area. The ultrasonic tracking system analyzes sound communications to determine the distances between the game system and each controller and to determine the distances among the controllers. The distances are then analyzed by the game interface to calculate the depths within the capture area for each controller.

In accordance with the present invention there is provided methods for generating an isotropic or near-isotropic three-dimensional images from two-dimensional images. In accordance with the present invention the method includes, obtaining a first image of a body part in a first plane, wherein the first image generates a first image data volume; obtaining a second image of the body part in a second plane, wherein the second image generates a second image data volume; and combining the first and second image data volumes to form a resultant image data volume, wherein the resultant image data volume is isotropic or near-isotropic.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

The availability of high quality imagers on smartphones and other portable devices facilitates creation of a large, crowd-sourced, image reference library that depicts skin rashes and other dermatological conditions. Some of the images are uploaded with, or later annotated with, associated diagnoses or other information (e.g., “this rash went away when I stopped drinking milk”). A user uploads a new image of an unknown skin condition to the library. Image analysis techniques are employed to identify salient similarities between features of the uploaded image, and features of images in this reference library. Given the large dataset, statistically relevant correlations emerge that identify to the user certain diagnoses that may be considered, other diagnoses that may likely be ruled-out, and / or anecdotal information about similar skin conditions from other users. Similar arrangements can employ audio and / or other physiologically-derived signals. A great variety of other features and arrangements are also detailed.

Synchronizes a secondary audio track to a video. Analyzes at least one track of a video using audio frequency analysis or spectrograms, image analysis or text analysis to find distinct audio / image / caption events from which to ensure synchronization of a secondary audio track. For example, commentary that mocks a character may be played immediately after a particular noise in the audio track of a video occurs such as a door slam. Keeping the secondary audio track in synch with the audio track of a video is performed by periodically searching for distinct events in a track of a video and adjusting the timing of the secondary audio track. May utilize a sound card on a computer to both analyze a DVD sound track and play and adjust timing of the secondary audio track to maintain synchronization. Secondary audio tracks may be purchased and / or downloaded and utilized to add humorous external commentary to a DVD for example.

A system, method and device for the capture and display of high-resolution stereoscopic or monoscopic wide fields-of-view (FOV) at still or video rates, presenting techniques and designs for distance measuring, for changing the working stereo capture range of a stereoscopic image capture device, and for playing pre-recorded or transmitted stereoscopic video image data through a player unit. The system supports multiple independent viewers and image analysis sub-systems of various types utilizing hardware, software and firmware. Further included is a stereoscopic videoconferencing embodiment that captures and transmits an entire room's view and automatically directs focus of images.

Apparatuses and methods for mobile imaging and image analysis. In particular, described herein are methods and apparatuses for assisting in the acquisition and analysis of images of the tympanic membrane to provide information that may be helpful in the understanding and management of disease, such ear infection (acute otitis media). These apparatuses may guide or direct a subject in taking an image of a tympanic membrane, including automatically detecting which direction to adjust the position of the apparatus to capture an image of the tympanic membrane and automatically indicating when the tympanic membrane has been imaged.

The invention relates to a visual recognition and positioning method for robot intelligent capture application. According to the method, an RGB-D scene image is collected, a supervised and trained deep convolutional neural network is utilized to recognize the category of a target contained in a color image and a corresponding position region, the pose state of the target is analyzed in combinationwith a deep image, pose information needed by a controller is obtained through coordinate transformation, and visual recognition and positioning are completed. Through the method, the double functions of recognition and positioning can be achieved just through a single visual sensor, the existing target detection process is simplified, and application cost is saved. Meanwhile, a deep convolutional neural network is adopted to obtain image features through learning, the method has high robustness on multiple kinds of environment interference such as target random placement, image viewing anglechanging and illumination background interference, and recognition and positioning accuracy under complicated working conditions is improved. Besides, through the positioning method, exact pose information can be further obtained on the basis of determining object spatial position distribution, and strategy planning of intelligent capture is promoted.

A high resolution CMOS imaging system especially suitable for use in a periscope head. The imaging system includes a sensor head for scene acquisition, and a control apparatus inclusive of distributed processors and software for device-control, data handling, and display. The sensor head encloses a combination of wide field-of-view CMOS imagers and narrow field-of-view CMOS imagers. Each bank of imagers is controlled by a dedicated processing module in order to handle information flow and image analysis of the outputs of the camera system. The imaging system also includes automated or manually controlled display system and software for providing an interactive graphical user interface (GUI) that displays a full 360-degree field of view and allows the user or automated ATR system to select regions for higher resolution inspection.

Spatially Integrated Small-Format Aerial Photography (SFAP) is one aspect of the present invention. It is a low-cost solution for bridge surface imaging and is proposed as a remote bridge inspection technique to supplement current bridge visual inspection. Providing top-down views, the airplanes flying at about 1000 feet can allow visualization of sub-inch (large) cracks and joint openings on bridge decks or highway pavements. On board Global Positioning System (GPS) is used to help geo-reference images collected and facilitate damage detection. Image analysis is performed to identify structural defects such as cracking. A deck condition rating technique based on large crack detection is used to quantify the condition of the existing bridge decks.

A method of providing rapid business support of insured property using image analysis can include the step of receiving at least one digital image of damaged property. Damage can be automatically accessed for insurance purposes based upon the received images. An incident response can be automatically determined based at least in part upon the damage assessment. Incident responses can include, but are not limited to, tendering a claim payoff offer, referring a claim to a human agent, providing repair instructions, and / or arranging for a physical damage assessment of the damaged property.

The enumeration of cells in fluids by flow cytometry is widely used across many disciplines such as assessment of leukocyte subsets in different bodily fluids or of bacterial contamination in environmental samples, food products and bodily fluids. For many applications the cost, size and complexity of the instruments prevents wider use, for example, CD4 analysis in HIV monitoring in resource-poor countries. The novel device, methods and algorithms disclosed herein largely overcome these limitations. Briefly, all cells in a biological sample are fluorescently labeled, but only the target cells are also magnetically labeled. The labeled sample, in a chamber or cuvet, is placed between two wedge-shaped magnets to selectively move the magnetically labeled cells to the observation surface of the cuvet. An LED illuminates the cells and a CCD camera captures the images of the fluorescent light emitted by the target cells. Image analysis performed with a novel algorithm provides a count of the cells on the surface that can be related to the target cell concentration of the original sample. The compact cytometer system provides a rugged, affordable and easy-to-use technique, which can be used in remote locations.

The present invention is a method and system for automatically analyzing a category in a plurality of the categories in a physical space based on the visual characterization, such as behavior analysis or segmentation, of the persons with regard to the category. The present invention captures a plurality of input images of the persons in the category by a plurality of means for capturing images. The present invention processes the plurality of input images in order to understand the shopping behavior of the persons with the sub-categories of the category and analyzes the level of engagement and decision process at the sub-category level. The processes are based on a novel usage of a plurality of computer vision technologies to analyze the visual characterization of the persons from the plurality of input images. The physical space may be a retail space, and the persons may be customers in the retail space.

The present invention relates to methods and systems for conducting three-dimensional image analysis and diagnosis and possible treatment relating thereto. The invention includes methods of handling signals containing information (data) relating to three-dimensional representation of objects scanned by a scanning medium. The invention also includes methods of making and analyzing volumetric measurements and changes in volumetric measurements which can be used for the purpose of diagnosis and treatment.

Image analysis techniques, including object recognition analysis, are applied to images obtained by one or more image capture devices deployed within inventory environments. The object recognition analysis provides object recognition data (that may include one or more recognized product instances) based on stored product (training) images. In turn, a variety of functionalities may be enabled based on the object recognition data. For example, a planogram may be extracted and compared to a target planogram, or at least one product display parameter for a product can be determined and used to assess presence of the product within the inventory environment, or to determine compliance of display of the product with a promotional objective. In yet another embodiment, comparisons may be made within a single image or between multiple images over time to detect potential conditions requiring response. In this manner, efficiency and effectiveness of many previously manually-implemented tasks may be improved.

A system for broad area geospatial object recognition, identification, classification, location and quantification, comprising an image manipulation module to create synthetically-generated images to imitate and augment an existing quantity of orthorectified geospatial images; together with a deep learning module and a convolutional neural network serving as an image analysis module, to analyze a large corpus of orthorectified geospatial images, identify and demarcate a searched object of interest from within the corpus, locate and quantify the identified or classified objects from the corpus of geospatial imagery available to the system. The system reports results in a requestor's preferred format.