Abstract: There is provided a barcode detection device including an image sensor and a processor. The image sensor captures an image frame of a barcode. The processor calculates a gradient vector of bars of the barcode in the image frame for determining a rotation angle of the image sensor. The rotation angle is used to calibrate a detected bar width.

Abstract: An image processing apparatus includes a low-resolution image generating circuit configured to generate a low-resolution image including a second pixel corresponding to first pixels based on an input image including the first pixels, and an edge preserving smoothing circuit configured to generate a reliability of the second pixel based on characteristics of values of the first pixels and perform edge preserving smoothing on the input image using a value of the second pixel of which a reflection ratio is adjusted, based on the reliability of the second pixel.

Abstract: A display may display a region of an anatomy that is not within the field of effect of an instrument. The additional views may assist in determining a location and orientation of an instrument. The instrument may be tracked with a tracking system to make the determination of image data to display.

Abstract: Training a descriptor network includes obtaining a first image of a scene from an image capture device, applying a sensor sensitivity model to the first image to obtain shadow-invariant image data for the first image, and selecting a first patch from the image. Training a descriptor network also includes obtaining a subset of the shadow-invariant image data corresponding to the first patch, and training the descriptor network to provide localization data based on the first patch and the subset of the shadow-invariant image data.

Abstract: A wafer backside defect detection method and a wafer backside defect detection apparatus are provided. The wafer backside defect detection method includes the following steps. A peripheral edge area of a wafer backside image that at least one notch is located is cropped off. Adjacent white pixels on the wafer backside image are connected to obtain a plurality of abnormal regions. If a total area of top N of the abnormal regions is more than 10% of an area of the wafer, it is deemed that the wafer has a roughness defect. N is a natural number. If the total area of the top N of the abnormal regions is less than 1% of the area of the wafer and a largest abnormal region of the abnormal regions is longer than a predetermined length, it is deemed that the wafer has a scratch defect.

Abstract: Various embodiments are directed to a device including an infrared phase detection autofocus (PDAF) sensor. The device may include a projector configured to transmit a source light onto a scene. The device may include the infrared PDAF sensor configured to receive reflections of the source light off of objects within the scene. The infrared PDAF sensor may include a first set of pixels including focus pixels. The device may include a processor coupled to the infrared PDAF sensor and a memory. The processor may be configured to generate first depth data based on the received reflections of the source light. The processor may be configured to generate second depth data based on signals generated from corresponding pairs of the focus pixels. The processor may be configured to generate combined depth data based on the first depth data and the second depth data.

Abstract: A vehicle includes: a first camera mounted on the vehicle to have a first field of view and configured to acquire first image data; a second camera mounted on the vehicle to have a second field of view and configured to acquire second image data; a display; and a controller. The controller is configured to display around-view data in which the first image data and the second image data are combined so that a boundary between the first image data and the second image data becomes a first reference angle on the display. The controller is also configured to display around-view data in which the first image data and the second image data are combined so that a boundary between the first image data and the second image data becomes a second reference angle on the display based on an obstacle located around the vehicle.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying high-priority agents in the vicinity of a vehicle and, for only those agents which are high priority agents, generating data characterizing the agents using a first prediction model. In a first aspect, a system identifies multiple agents in an environment in a vicinity of a vehicle. The system generates a respective importance score for each of the agents by processing a feature representation of each agent using an importance scoring model. The importance score for an agent characterizes an estimated impact of the agent on planning decisions generated by a planning system of the vehicle which plans a future trajectory of the vehicle. The system identifies, as high-priority agents, a proper subset of the plurality of agents with the highest importance scores.

Abstract: Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data.

Abstract: Image processing methods, devices, and storage media are provided. One of the image processing methods includes: obtaining an image comprising a target object; inputting the image into a mask prediction model to obtain a first mask image corresponding to the target object in the image; inputting the first mask image and the image comprising the target object into a mask quality unification model to obtain a second mask image, wherein the mask quality unification model is configured to adjust a fineness associated with the first mask image to a target fineness to obtain the second mask image, and wherein the second mask image has image semantic information consistent with image semantic information of the image comprising the target object; and inputting the image comprising the target object and the second mask image into a target image obtaining model to obtain a target image corresponding to the target object.

Abstract: A driving environment information display method includes acquiring environment information; selecting a first seed image corresponding to curvature of a road on which driving is currently performed based on the acquired environment information, from among a plurality of lane division line seed images having different curvatures; disposing two of the selected first seed image at a display origin corresponding to a vehicle origin; distorting one of the two first seed images based on a first lateral distance from a left lane division line of a lane on which a host vehicle drives; distorting the other of the two first seed images based on a second lateral distance from a right lane division line of the lane; and outputting each of the two distorted first seed images through a display unit.

Abstract: A method and system for image processing is provided. The method for image processing may include: obtaining an image data set, wherein the image data set includes a first set of volume data; and determining, by the at least one processor, a target anatomy of interest based on the first set of volume data. The determining of the target anatomy of interest may include: determining an initial anatomy of interest in the first set of volume data; and editing the initial anatomy of interest to obtain the target anatomy of interest. The target anatomy of interest may include at least one region of interest (ROI) or at least one volume of interest (VOI). The initial anatomy of interest may include at least one ROI or at least one VOI.

Abstract: A media playout system receives a broadcast log transmitted from a media scheduling system. The broadcast log includes a restricted show, and the media playout system makes a first determination a blackout period assigned to the restricted show. The blackout period indicates a period of time associated with the restricted show during which at least one media item is prohibited from being scheduled. The media player also determines that the broadcast log indicates that the at least one media item has been improperly scheduled during the blackout period. In response to determining that the at least one media item has been improperly scheduled during the blackout period, the media playout system transmits, to the media scheduling system, a message requesting a replacement media item to replace the at least one media item that has been improperly scheduled during the blackout period.

Abstract: A method includes receiving a histogram output from a detector sensor, and calculating a median point of a pulse waveform within the histogram. The pulse waveform has an even probability distribution over at least one quantization step of the histogram around the median point. A corresponding apparatus can include a detector sensor and a co-processor coupled to the detector sensor.

Abstract: The disclosure relates to testing software for operating an autonomous vehicle. In one instance, a simulation may be run using log data collected by a vehicle operating in an autonomous driving mode. The simulation may be run using the software to control a simulated vehicle and by modifying a characteristic of an agent identified in the log data. During the running of the simulation, that a first type of interaction between the first simulated vehicle and the modified agent will occur may be determined. In response to determining that the particular type of interaction will occur, the modified agent may be replaced by a interactive agent that simulates a road user corresponding to the modified agent that is capable of responding to actions performed by simulated vehicles. That the particular type of interaction between the simulated vehicle and the interactive agent has occurred in the simulation may be determined.

Abstract: Improving the accuracy of predicted segmentation masks, including: extracting a ground-truth RGB image buffer and a binary contour image buffer from a ground-truth RGB image container for segmentation training; generating predicted segmentation masks from the ground-truth RGB image buffer; generating second binary contours from the predicted segmentation masks using a particular algorithm; computing a segmentation loss between manually-segmented masks of the ground-truth RGB image buffer and the predicted segmentation masks; computing a contour accuracy loss between contours of the binary contour image buffer and the binary contours of the predicted segmentation masks; computing a total loss as a weighted average of the segmentation loss and the contour accuracy loss; and generating improved binary contours by compensating the contours of the binary contour image buffer with the computed total loss, wherein the improved binary contours are used to improve the accuracy of the predicted segmentation masks.

Abstract: A system and method for concealing sensitive information may include: receiving a screenshot from an application; generating an application model that identifies the application by automatically determining a respective position or location of part(s) of the screenshot; determining a part of the screenshot includes sensitive information, automatically concealing the sensitive information in the screenshot based application model to thus generate a modified screenshot, and recording the modified screenshot.

Abstract: Methods and systems are provided for transforming sketches into stylized electronic paintings. A neural network system is trained where the training includes training a first neural network that converts input sketches into output images and training a second neural network that converts images into output paintings. Similarity for the first neural network is evaluated between the output image and a reference image and similarity for the second neural network is evaluated between the output painting, the output image, and a reference painting. The neural network system is modified based on the evaluated similarity. The trained neural network is used to generate an output painting from an input sketch where the output painting maintains features from the input sketch utilizing an extrapolated intermediate image and reflects a designated style from the reference painting.

Abstract: Systems and methods for training machine learning models based on domain constraints are disclosed. An example method includes receiving a plurality of images, each image associated with a cluster of a plurality of clusters, the plurality of clusters representing an output of a second machine learning model, assigning a label to each cluster of the plurality of clusters based at least in part on a plurality of constraints, identifying, based at least in part on the plurality of constraints, a first label mismatch for a first image, the first label mismatch indicating that the first image belongs to a first cluster but should be assigned to a second cluster different from the first cluster, reassigning the first image to the second cluster, and training the first machine learning model, based on the labeled clusters of the plurality of clusters, to predict labels associated with subsequently received image data.

Abstract: A method for determining a quantity of interest related to the density of organic tissue starts with a digital representation of a histological image of the tissue. The digital representation is converted to a binary image, to discriminate pixels that represent tissue of interest in the image. A box filter is applied to values of the pixels of interest to obtain a tissue density value for each pixel of interest. A quantity of interest is computed, based upon the tissue density values for the pixels of interest. A tangible representation of the computed quantity of interest, such as a numerical value, a graph, or a color representation, is displayed or otherwise presented via an interface.

Abstract: Described are a method, apparatus and computer program product are provided for block modulating video and image compression. Different masks may be imposed on different blocks of an image and then the blocks summed to one block. In some embodiments, an encoder complexity of the encoder may be O(1). A method can be carried out that includes dividing an input image into a plurality of blocks; assigning different masks to each respective image block of the plurality of image blocks, the different masks having a size equal to that of each respective image block of the plurality of image blocks; modulating each respective image block of the plurality of blocks the assigned different masks to generate a plurality of modulated image blocks; summing the modulated plurality of blocks to at least one summed block; and quantizing the at least one summed block.

Abstract: The present disclosure relates to devices and methods for determining new virtual evidence to use with a deep probabilistic logic module. The devices and methods may receive output from a deep probabilistic logic module in response to running an initial set of virtual evidence through the deep probabilistic logic module. The devices and methods may use the output to automatically propose at least one factor as new virtual evidence for use with the deep probabilistic logic module. The devices and methods may add the new virtual evidence to the deep probabilistic logic module.

Abstract: Techniques facilitating resolution-based spatial computing are provided. In one example, a computer-implemented method comprises traversing, by a device operatively coupled to a processor, a data structure corresponding to a land area for a location having an index; and determining, by the device, whether the location is at least partially within the land area based on a result of the traversing. In some embodiments, the traversing comprises: obtaining a threshold number of levels based at least in part on a resolution parameter; scanning a first level of the data structure for a node having an index corresponding to the index of the location; and iterating the scanning for respective subsequent levels of the data structure based on the scanning returning a node having subordinate nodes and a number of levels for which the scanning and iterating have been performed being less than the threshold number of levels.

Abstract: A method for detecting defects in a near-eye display is provided. The method includes the following steps: obtaining a reference image and a DUT image according to a first image and a second image captured by a camera through a Fresnel lens when a display panel respectively displays a test-pattern image and a test-background image; performing a fast Fourier transform on the reference image and the DUT image to obtain a frequency-domain reference image and a frequency-domain DUT image; calculating an average value of pixel values above a predetermined cut-off ratio in a histogram of each first region of interest (ROI) in a filtered frequency-domain reference image as a corresponding threshold; comparing each pixel in the filtered DUT image with the corresponding threshold to generate a determination result; and building a defective-status map of the near-eye display according to the determination results.

Abstract: An appropriate peak detection is performed on the basis of a histogram indicating a frequency of reception of reflected light to measure a distance to a target object. A histogram acquisition unit acquires a histogram indicating the frequency of reception of reflected light including active light components that are active light emitted from a light emitting unit and reflected by the target object and ambient light components that are ambient light reflected by the target object. A detection unit detects a distribution of the active light components by performing predetermined statistical processing on the histogram. A measurement unit measures the distance to the target object as distance information on the basis of the distribution of the active light components.

Abstract: A system and method for geolocation-based pictographs are provided. In example embodiments, a current geolocation of a user device is determined. A pictograph is identified based on the current geolocation of the user device. The identified pictograph is presented on a user interface of the user device.

Abstract: A computer-implemented method of using augmented reality (AR) to detect a plane and a spatial configuration of an object, the method comprising the steps of detecting one or more edges of the object; identifying one or more lines of the object; filtering the one or more lines of the object; iteratively approximating one or more distributions of the one or more lines; and determining boundaries of the object.

Abstract: A reading portion generates an original image including an image of a document sheet. A first document sheet end detection portion, in a case where the thickness of the document sheet is equal to or greater than a threshold value, identifies a peripheral edge shape of the document sheet by detecting a shadow portion that occurs at a peripheral edge portion of the document sheet in the original image. A second document end detection portion, in a case where the thickness of the document sheet is less than a threshold value, identifies the peripheral edge shape based on a specification by the user. A document sheet size determination portion determines a size of the document sheet according to a result of shape identification by the first document sheet end detection portion or a result of shape identification by the second document sheet end detection portion.

Abstract: Various embodiments are described that relate to an adaptive learning system. The adaptive learning system can be trained by correlation between a first set of raw technical performance data and a set of actual operational effectiveness assessment data. Once trained, the adaptive learning system can be deployed. Once deployed, the adaptive learning system can produce a set of predicted operational effectiveness assessment data from a second set of raw technical performance data that is different from the first set of raw technical performance data.

Abstract: Various tray inserts, methods and algorithm for certifying candidate trays for use in an X-ray scanner system are discussed. The tray insert includes at least a body having multiple parts positioned for generation of image quality metrics for tray impact evaluation in; a first cover and a second cover disposed at opposite ends to fix and secure the body. The method including running an algorithm to control an X-ray system to collect baseline image data from certified trays, collecting candidate tray image data, extracting image quality metrics for both the baseline image data and the candidate tray image data, and performing statistical analysis using and comparing image quality metrics from the baseline image data and the candidate tray image data to certify the candidate tray based on the statistical and comparison results.

Abstract: Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data.

Abstract: Apparatuses, systems, and techniques to generate blue noise masks for real-time image rendering and enhancement. In at least one embodiment, a vector-valued noise mask is generated and applied to one or more images to generate one or more enhanced images for image processing (e.g., real-time image rendering). In at least one embodiment, the noise mask includes vector values per pixel and is able to handle the temporal domain (e.g., add time to the spatial domain) to improve image quality when rendering images over multiple frames.

Abstract: A method, including: recording plural images of an object by scanning plural particle beams across the object and detecting signals generated by the particle beams, wherein the plural particle beams are generated by a multi-beam particle microscope; determining plural regions of interest; determining plural image regions in each of the recorded images; determining plural displacement vectors; and determining image distortions based on image data of the recorded images and the determined displacement vectors.

Abstract: A system and method for error correction for machine-readable symbols having data codewords, and having error correction (EC) codewords derived from the data codewords and redundantly indicating the location and data contents of the data codewords. The symbols use Reed-Solomon (RS) error correction to retrieve damaged codewords. RS error correction normally requires two EC codewords to identify both the location and data contents of a data codeword. The present system and method perform optical contrast analysis on the codewords, identifying those codewords with the lowest contrast levels. Codewords with the lowest contrast levels are flagged as optically ambiguous, thereby marking, in the EC equations, the locations of the codewords most like to be in error. As a result, only a single EC codeword is required to retrieve the data for a flagged data codeword.

Abstract: An information processing device executes: acquiring a scanned image of a document and a protective sheet that protects the document, the scanned image being obtained by imaging the document and the protective sheet while being conveyed at the same time; acquiring a first length that is a conveying direction length of a predetermined portion of the protective sheet; acquiring a second length that is a conveying direction length of the predetermined portion in the scanned image; and estimating a ratio between a document length, which is a conveying direction length of the document, and a document image length, which is a conveying direction length of the document in the scanned image, based on the first length and the second length.

Abstract: Methods and apparatus for merging tasks in a graphics pipeline in which, subsequent to a trigger to flush a tag buffer, one or more tasks from the flushed tag buffer are generated, each task comprising a reference to a program and plurality of fragments on which the program is to be executed, wherein a fragment is an element of a primitive at a sample position. It is then determined whether merging criteria are satisfied and if satisfied, one or more fragments from a next tag buffer flush are added to a last task of the one or more tasks generated from the flushed tag buffer.

Abstract: Methods, devices and storage media for data processing are provided. One of the methods include: obtaining a target image, wherein the target image comprises at least one tubular image; determining a spatial distribution feature and an image feature of each of the at least one tubular image; obtaining, based on a tubular structure recognition model, at least one fusion feature respectively corresponding to the at least one tubular image by fusing the spatial distribution feature and the image feature of each of the at least one tubular image; and recognizing, based on the tubular structure recognition model and the at least one fusion feature respectively corresponding to the at least one tubular image, at least one tubular structure respectively corresponding to the at least one tubular image.

Abstract: An image processing method includes: generating, from combined connected components (CCs) of a document image, candidate text CCs, candidate background CCs, and candidate natural image CCs where the candidate background CCs are excluded from the combined CCs to generate the candidate natural image CCs with a predetermined criterion dependent on the candidate text CCs; generating a final natural image bounding box by expanding a candidate natural image bounding box of the candidate natural image CCs and including in the expanded candidate natural image bounding box at least one combined CC that intersects the expanded candidate natural image bounding box; and modifying, based on the final natural image bounding box, the document image and displaying the modified document image to a user.

Abstract: Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.

Abstract: A system is provided for the automated assembly of engine cylinder valves capable of registering a valve stem as a robot datum working location, placing a valve stem spring over the working location, compressing the valve stem spring onto the valve stem, inserting a valve keeper into a valve stem seating notch and locking the valve keeper with a cap by a computer controlled automated cylinder head assembly line. A spring feeding station registers the valve stem and said places the valve stem spring over the working location. A multi-axis mechanical robot grips the valve spring about its outer diameter with a gripping fixture from a spring feeding fixture forming an end effector incorporating a jaw gripper urged by a pneumatically actuator. A vision system locates a cylinder block on a transferred pallet to determine an X, Y, and Rz plane for placement of the valve, spring and spring keeper.

Abstract: A method includes generating a diffraction map from a plurality of target patterns, generating a favorable zone and an unfavorable zone from the diffraction map, placing a plurality of sub-resolution patterns in the favorable zone, and performing a plurality of geometric operations on the plurality of sub-resolution patterns to generate modified sub-resolution patterns. The modified sub-resolution patterns extend into the favorable zone, and are away from the unfavorable zone.

Abstract: Line-edge roughness or line width roughness is evaluated while preventing influence of noise caused by a device or an environment. Therefore, an averaged signal profile 405 in which a moving average of S pixels (S is an integer greater than 1) is taken in a Y direction is obtained from a signal profile showing a secondary electron signal amount distribution in an X direction with respect to a predetermined Y coordinate obtained from a top-down image, an edge position 406 of a line pattern is extracted based on the averaged signal profile, and a noise floor height is calculated based on a first power spectral density 407 of LER data or LWR data based on the extracted edge position and a second power spectral density 409 of a rectangular window function corresponding to the moving average of the S pixels.

Abstract: A display control unit displays a medical image from which at least one region of interest is extracted on a display unit. A correction unit corrects a boundary of the region of interest according to a correction instruction for the boundary of the region of interest extracted from the displayed medical image. An image generation unit generates a weighted image in which each pixel in the medical image has, as a pixel value of each pixel, a weight coefficient representing a weight of being within the region of interest, by setting an initial weight coefficient for the extracted region of interest and setting a corrected weight coefficient for a corrected region for which the correction instruction is given in the medical image.

Abstract: An approach is provided for using a machine learning model for identifying planar region(s) in an image. The approach involves, for example, determining the model for performing image segmentation. The model comprises at least: a trainable filter that convolves the image to generate an input volume comprising a projection of the image at different resolution scales; and feature(s) to identify image region(s) having a texture within a similarity threshold. The approach also involves processing the image using the model by generating the input volume from the image using the trainable filter and extracting the feature(s) from the input volume to determine the region(s) having the texture. The approach further involves determining the planar region(s) by clustering the image regions. The approach further involves generating a planar mask based on the planar region(s). The approach further involves providing the planar mask as an output of the image segmentation.

Abstract: An object identification and collection method is disclosed. The method includes receiving a pick-up path that identifies a route in which to guide an object-collection system over a target geographical area to pick up objects, determining a current location of the object-collection system relative to the pick-up path, and guiding the object-collection system along the pick-up path over the target geographical area based on the current location. The method further includes capturing images in a direction of movement of the object-collection system along the pick-up path, identifying a target object in the images; tracking movement of the target object through the images, determining that the target object is within range of an object picker assembly on the object-collection system based on the tracked movement of the target object, and instructing the object picker assembly to pick up the target object.

Abstract: Systems and method of identifying a horizon depicted in an image are presented herein. Information defining an image may be obtained. The image may include visual content comprising an array of pixels. The array may include pixel rows. Parameter values for a set of pixel parameters of individual pixels of the image may be determined. Individual average parameter values of the individual pixel parameters of the pixels in the individual pixel rows may be determined. Based on the average parameter values a pixel row may be identified as depicting a horizon in the image.

Abstract: Embodiments are directed to techniques for image content extraction. Some embodiments include extracting contextually structured data from document images, such as by automatically identifying document layout, document data, document metadata, and/or correlations therebetween in a document image, for instance. Some embodiments utilize breakpoints to enable the system to match different documents with internal variations to a common template. Several embodiments include extracting contextually structured data from table images, such as gridded and non-gridded tables. Many embodiments are directed to generating and utilizing a document template database for automatically extracting document image contents into a contextually structured format. Several embodiments are directed to automatically identifying and associating document metadata with corresponding document data in a document image to generate a machine-facilitated annotation of the document image.

Abstract: Embodiments of this application provide a method and an apparatus for determining drivable region information. The method includes obtaining first information, where the first information includes information about an initial drivable region determined based on at least one image, and the at least one image is from at least one camera module. The method also includes obtaining second information, where the second information includes radar detection information. The method further includes determining first drivable region information based on the first information and the second information.

Abstract: Certain aspects provide a method, including: receiving a depth image from a depth sensor; receiving a segmentation mask corresponding to the depth image and segmenting the depth image into a set of foreground pixels and a set of background pixels; determining a set of seed pixels in the depth image; for each respective seed pixel of the set of seed pixels: determining a sampling line in the depth image that starts at the respective seed pixel and passes through a portion of the depth image; for each respective sampling line pixel in the sampling line having a value in the segmentation mask indicating a foreground object in the depth image: determining one or more data attribute values based on a depth value for the respective sampling line pixel in the depth image; and adding the one or more data attribute values to a feature vector.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that utilize simultaneous, multi-mesh deformation to implement edge aware transformations of digital images. In particular, in one or more embodiments, the disclosed systems generates a transformation handle that targets an edge portrayed in a digital image. In some cases, the disclosed systems provide the transformation handle for display over the digital image. Additionally, in one or more embodiments, the disclosed systems generate vectors splines and meshes for the edge and one or more influenced regions adjacent to the edge. In response to detecting a user interaction with the transformation handle, the disclosed systems can modify the edge and the at least one influenced region by modifying the corresponding vector splines and meshes.