Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for on-shelf merchandise detection are provided. One of the methods includes: obtaining a plurality of depth images associated with a shelf from a first camera; obtaining a plurality of images from one or more second cameras associated with each of a plurality of tiers of the shelf; detecting motions of a user's hand comprising reaching into and moving away from the shelf; determining one of the tiers of the shelf associated with the detected motions, a first point of time associated with reaching into the shelf, and a second point of time associated with moving away from the shelf; identifying a first image captured before the first point in time and a second image captured after the second point in time; and comparing the first image and the second image to determine one or more changes to merchandise.

Abstract: A multi-label heat map display system is operable to receive a medical scan and a set of heat maps set of heat maps that each correspond to probability matrix data generated for each of a set of abnormality classes. An interactive interface that displays image data of the medical scan and at least one of the set of heat maps is generated for display on a display device associated with the multi-label heat map display system. User input to a client device is received, and an updated interactive interface that includes a change to the display of the at least one of the set of heat maps by the second portion of the interactive interface in response to the user input is displayed.

Abstract: A method for providing real time service of huge and high quality digital image on internet is disclosed, wherein data relevant to a general life such as a general photo, an advertising leaflet, and a pamphlet and professional image data exhibited in an art gallery, exhibition grounds, a pavilion are made into huge and high quality digital image or scanned and photographed to be digital, thereby processing real time service as an interactive browsing form. In the present invention, data are directly made, edited, constructed, and uploaded on internet, thereby providing various additional information with image through hyperlink and processing high quality digital image service on network without speed delay for huge image.

Abstract: A discrete wavelet transform (DWT) based generative system for generating images of fashion products is provided. The system includes a memory having computer-readable instructions stored therein. The system includes a processor configured to access a plurality of fashion images of a plurality of fashion products. Each fashion image is generated at a first resolution. The processor is configured to train one or more DWT based generative models using the plurality of fashion images of the fashion products. Each of the generative models is selectively trained using a directional fashion image. The directional fashion image includes details of the fashion products corresponding to a pre-determined orientation and scale. The processor is further configured to generate an upsampled fashion image corresponding to each of the fashion images. Each upsampled fashion image is generated at a second resolution.

Abstract: A method for image segmentation includes receiving an input image (102). The method further includes obtaining a deep learning model (104) having a triad of predictors (116, 118, 120). Furthermore, the method includes processing the input image by a shape model in the triad of predictors (116, 118, 120) to generate a segmented shape image (110). Moreover, the method includes presenting the segmented shape image via a display unit (128).

Abstract: Techniques are described for using machine learning (ML) models to create information technology (IT) infrastructures at a service provider network based on image of IT system architecture diagrams. To create IT system architecture diagrams, system architects often use tools ranging from pen and paper and whiteboards to various types of software-based drawing programs. Based on a user-provided image of an IT system architecture diagram (for example, a digital scan of a hand drawn system diagram, an image file created by a software-based drawing program, or the like), a service provider network uses one or more ML models to analyze the image to identify the constituent elements of the depicted IT system architecture and to create an infrastructure template that can be used to automatically provision corresponding computing resources at the service provider network.

Abstract: A method for displaying a sequence of review images related to a structure, said method comprising: receiving (501) a review target (313) for the structure and an environmental factor (305) affecting at least one property of the structure; selecting (503), from a plurality of captured images related to the structure, a plurality (321) of review images of at least a part of the structure based on the review target, the environmental factor and position information associated with the review images with respect to the structure; and causing a display device to display the selected review images ordered according to the review target to form the sequence of review images.

Abstract: A method of performing loop closure detection is described. The method comprises detecting a movement of a device having a camera; and adaptively disabling or enabling, using a processor of the device, a loop closure detection of the device based upon the detected movement of the device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for on-shelf merchandise detection are provided. One of the methods includes: obtaining a plurality of depth images associated with a shelf from a first camera; obtaining a plurality of images from one or more second cameras associated with each of a plurality of tiers of the shelf; detecting motions of a user's hand comprising reaching into and moving away from the shelf; determining one of the tiers of the shelf associated with the detected motions, a first point of time associated with reaching into the shelf, and a second point of time associated with moving away from the shelf; identifying a first image captured before the first point in time and a second image captured after the second point in time; and comparing the first image and the second image to determine one or more changes to merchandise.

Abstract: A defect inspection device includes an image sensor configured to obtain an image of a target region of an object and divide the image of the target region into an array of pixels, and a processor. The processor is configured to receive a signal indicating a value of a property of the divided image, select a first pixel in the divided image, determine the value of the property of the first pixel, determine a reference pixel value for the first pixel, compare the reference pixel value to the value of the first pixel to obtain a difference value, and set a threshold difference at which a defect is assessed to be present, based at least in part on the value of the property of second pixels in the divided image adjacent to the first pixel.

Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

Abstract: A method that includes obtaining, using a processor, image data from a target coating. The method also includes performing, using the processor, an image analysis to determine at least one sparkle point from the image data, and performing, using the processor, a hue analysis to determine a sparkle color from the sparkle point. The method further includes calculating, using the processor, a sparkle color distribution, and generating, using the processor, a coating formulation that is the same or substantially similar in appearance to the target coating.

Abstract: An image encoder includes a processor and a memory. The memory includes instructions configured to cause the processor to perform operations. In one example implementation, the operations may include determining whether a dictionary item is available for replacing a block of an image being encoded, the determining based on a hierarchical lookup mechanism, and encoding the image along with reference information of the dictionary item in response to determining that the dictionary item is available. In one more example implementation, the operations may include performing principal component analysis (PCA) on a block to generate a corresponding projected block, the block being associated with a group of images, comparing the projected block with a corresponding threshold, descending the block recursively based on the threshold until a condition is satisfied, and identifying a left over block as a cluster upon satisfying of the condition.

Abstract: A method of converting a wide dynamic range (WDR) image to a low dynamic range (LDR) image have the steps of: (i) obtaining a transfer function that has a plurality of sub-functions, each sub-function corresponding to a non-overlapped input interval of the dynamic range of the WDR image; (ii) determining the intensity of each pixel of the LDR image by using the transfer function and at least the intensity value of the corresponding pixel of the WDR image; and (iii) outputting the LDR image.

Abstract: An image processing apparatus according to an embodiment has processing circuitry configured to acquire three-dimensional medical image data; set coordinates of at least two or more elements to evaluate an evaluation target represented by the three-dimensional medical image data, on images of different positioning slices of the three-dimensional medical image data; calculate a measured value for evaluating the evaluation target based on the coordinates; and control a display to display the measured value.

Abstract: Provided are a microneedle array imaging device, a microneedle array imaging method, a microneedle array inspection device, and a microneedle array inspection method which enable inspection of a microneedle array with high accuracy based on an obtained image. A microneedle array 1 is imaged from a side of a surface on which microneedles 2 are arranged by irradiating a surface on a side opposite to the surface on which the microneedles 2 are arranged with parallel light as illumination light. At this time, the surface is irradiated with the illumination light under conditions in which an incident angle ? of light onto a bottom surface 2a of the microneedle 2 is 90??° or greater and an incident angle ? of light onto a side surface 2b of the microneedle 2 is less than a critical angle ?. In this manner, a state in which almost no light is emitted from a tip portion of the microneedle 2 can be generated.

Abstract: In order to acquire height information regarding a subject disposed on the internal surface of an elongated tubular member, an image processing apparatus according to the present disclosure, includes a processor the processor including hardware and configured to perform the steps of receiving a first image and a second image acquired from a subject using an optical system having a field of view in a direction of at least about 90° to a central axis of the optical system, the first image acquired at a first position, the second image acquired at a second position, the second position different from the first position along the central axis; and calculating a distance between the subject and the central axis of the optical system, based on a distance between the first position and the second position, and based on the corresponding points in the third image and in the fourth image.

Abstract: Systems and methods for automated segmentation of anatomical structures (e.g., heart). Convolutional neural networks (CNNs) may be employed to autonomously segment parts of an anatomical structure represented by image data, such as 3D MRI data. The CNN utilizes two paths, a contracting path and an expanding path. In at least some implementations, the expanding path includes fewer convolution operations than the contracting path. Systems and methods also autonomously calculate an image intensity threshold that differentiates blood from papillary and trabeculae muscles in the interior of an endocardium contour, and autonomously apply the image intensity threshold to define a contour or mask that describes the boundary of the papillary and trabeculae muscles. Systems and methods also calculate contours or masks delineating the endocardium and epicardium using the trained CNN model, and anatomically localize pathologies or functional characteristics of the myocardial muscle using the calculated contours or masks.

Abstract: A method of generating a vehicle environment view for a vehicle, having has the following steps. Camera images are provided by vehicle cameras on the body of the vehicle. A vehicle environment view is calculated based on the camera images. A texture of a ground surface that is located below the vehicle body and is not visible to the cameras, is determined within the vehicle environment view by performing a local color prediction and a movement-compensated texture prediction.

Abstract: A method, system and computer readable medium for providing information about a region of a sample. The method includes (i) obtaining, by an imager, multiple images of the region; wherein the multiple images differ from each other by at least one parameter (ii) receiving or generating multiple reference images; (iii) generating multiple difference images that represent differences between the multiple images and the multiple reference images; (iv) calculating a set of region pixel attributes, (v) calculating a set of noise attributes, based on multiple sets of region pixels attributes of the multiple region pixels; and (vi) determining for each region pixel, whether the region pixel represents a defect based on a relationship between the set of noise attributes and the set of region pixel attributes of the pixel.