Abstract: The present disclosure relates to a vehicle image processing device and a method therefor. A vehicle image processing apparatus may include a storage that stores optical property information of a first camera among a plurality of cameras for obtaining a vehicle periphery image, a processor that determines whether backlight is present in the vehicle periphery image and generates a display image based on whether the backlight is present, and a communication device controlled by the processor and communicating with a device in the vehicle. The processor may calculate location information of a light source for at least one of the first camera or the vehicle by using coordinates of a shadow object of the vehicle, which is recognized from the vehicle periphery image, and coordinates of the vehicle, and may determine whether the backlight is present, by comparing location information of the light source with the optical property information.

Abstract: An automated optical inspection method, an automated optical inspection system, and a storage medium are provided. The method includes the following. An original image including first images of a target object is captured by an optical lens. An edge detection is performed on the original image to obtain an edge image including second images having an edge pattern. At least one of maximum, minimum, and average values of a pixel value in the second images is calculated. The edge image is divided into image blocks according to a unit area, and characteristic values are calculated according to the at least one of the maximum, minimum, and average values corresponding to the second images included in the image blocks. An optimal regression model is obtained by training a regression model corresponding to a defect of the target object according to the characteristic values and a data of the target object.

Abstract: The present invention relates to a device, system and method for pulsatility detection.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: The systems and methods provide a machine learning model that can exploit long time dependency for time-series sequences, perform end-to-end learning of dimension reduction and clustering, or train on long time-series sequences with low computation complexity. For example, the methods and systems use a novel, unsupervised temporal representation learning model. The model may generate cluster-specific temporal representations for long-history time series sequences and may integrate temporal reconstruction and a clustering objective into a joint end-to-end model.

Abstract: Methods and apparatus to determine engagement levels of audience members are disclosed. An example apparatus includes means for detecting whether an environment associated with a first device includes a second device with a display that is illuminated. The example apparatus also includes means for calculating an engagement of a user with respect to the first device based on a proximity between the user and the illuminated display.

Abstract: Methods, systems, and devices for displaying additional or targeted content to a user are disclosed. An image or data capture device associated with a display device may capture an image of a space associated with the user or capture data related to what is being viewed by the viewer's eyes. Objects in the captured image or objects being viewed may be recognized, including any identifiable image, item, detail, or article and the like. A recognized object may then be compared to a target list to determine a match. If matched, and if there is additional content associated with the target object, the additional content may be presented to the user.

Abstract: A method for enhancing liveness detection of image data is provided that includes receiving image data of a person and using multi-resolution convolution and octave convolution techniques to extract first and second frequency components from the received image data. The method also includes comparing the first frequency component against data in a first frequency map and comparing the second frequency component against data in a second frequency map. Furthermore, the method includes determining whether the first frequency component satisfies matching criteria with data in the first frequency map and determining whether the second frequency component satisfies matching criteria with data in the second frequency map. In response to determining the first and second frequency components fail to satisfy the data in the respective frequency map, the method concludes that the received image data was not taken of a live person.

Abstract: A system including a point monitor case including a point monitoring case port electrically coupled to a confined space monitoring device for acquiring monitoring data from a confined space. A centralized monitoring station cabinet communicatively connected to the point monitor case includes a display device, a processor, and a centralized monitoring application. The centralized monitoring application executes instructions on the processor to display: a number of workers in proximity to the confined space, a camera feed from a camera located at a confined space, a control button configured to control the confined space monitoring device, and gas sensor indicators. A hub is communicatively interposed between the point monitor case and the centralized monitoring station cabinet. The hub includes a cableless access point, an aggregator, and a graphical user interface configured to display an aggregated current state of the confined space, including a combination of data streams aggregated by the aggregator.

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for determining multi-term contextual tags for digital content and propagating the multi-term contextual tags to additional digital content. For instance, the disclosed systems can utilize search query supervision to determine and associate multi-term contextual tags (e.g., tags that represent a specific concept based on the order of the terms in the tag) with digital content. Furthermore, the disclosed systems can propagate the multi-term contextual tags determined for the digital content to additional digital content based on similarities between the digital content and additional digital content (e.g., utilizing clustering techniques). Additionally, the disclosed systems can provide digital content as search results based on the associated multi-term contextual tags.

Abstract: In an analyzer, an image processing unit performs processing of: dividing a measurement image into a plurality of partial measurement images, and dividing a reference image into a plurality of partial reference images; calculating a positional deviation amount of each of the partial measurement images relative to a corresponding partial reference image among the partial reference images; determining whether the positional deviation amount is a threshold or less; and correcting positional deviation of the measurement image based on the positional deviation amounts of the plurality of partial measurement images when the image processing unit has determined that the positional deviation amount is not the threshold or less.

Abstract: Disclosed is a method for transmitting data via a vehicle data bus from an ultrasonic system, which comprises at least one ultrasonic transmitter and an ultrasonic receiver, to a data processing device, wherein predetermined signal profile characteristics are extracted from the echo signal received by the at least one ultrasonic receiver of the ultrasonic system. Echo signal data, which represent signal profile characteristics extracted from the echo signal, is created. Said echo signal data is transmitted from the ultrasonic system via the vehicle data bus to the data processing device.

Abstract: Methods and apparatus to capture images are disclosed. An example apparatus disclosed herein includes an image sensor to observe a first image of a face, and a logic circuit to determine whether the face in the first image is in a first orientation with respect to the image sensor, and when the face in the first image is in the first orientation: trigger the image sensor to capture a second image of the face, and perform a facial recognition process on the second image, but not on the first image.

Abstract: Techniques for detecting anomalies in multispectral image data, and more specifically for detecting presentation attacks by using multispectral image data in biometric security applications, are provided. In some embodiments, a system may receive multispectral image data and generate an estimation of a first image of a plurality of images of the multispectral image data, wherein the estimation is based on other images of the multispectral image data, but not the first image itself. The estimation may then be compared to the first image to generate an indication as to whether the multispectral image data represents a presentation attack. In some embodiments, a system may receive multispectral training image data and may extract features from the data to generate and store a network architecture for predicting relationships of multispectral images of subjects.

Abstract: An electronic device includes a display screen that includes a cover glass, and a display illumination layer. The display illumination layer includes an array of light-emitting elements that forms an array of pixels of the display screen. The electronic device further includes a light source disposed adjacent the cover glass and configured to emit a light beam to be coupled into the cover glass. A portion of the light beam may be transmitted through the top surface of the cover glass to illuminate a hand of a user. The electronic device further includes an optical ID sensing module that includes an array of photodetectors disposed under the array of light-emitting elements and spatially distributed across the array of pixels of the display screen, and electronic circuitry coupled to the array of photodetectors and configured to capture a fingerprint image or a palmprint image of the hand.

Abstract: A discrimination device includes a sub-data set extraction unit for extracting from a plurality of labeled learning data a sub-learning data set to be used for learning and a sub-verification data set to be used for verification, a learning unit for performing supervised learning on the basis of the sub-learning data set to generate a pre-trained model for discriminating a label from data related to an object, a discrimination unit for conducting a discrimination processing using the pre-trained model on each piece of learning data contained in the sub-verification data set, a verification result recording unit for recording a result of the discrimination processing in association with the learning data, and a correctness detection unit for detecting learning data attached with a label that may be incorrect based on the discrimination processing results recorded in association with respective learning data.

Abstract: A heuristic engine includes capabilities to collect an unstructured data set, including document image data and correlate the image data with known valid data to detect document fraud. Notifications of fraud detection may include particular signature images, or characteristics of a document image. By feeding back indications of document fraud with correlations to past instances of fraud into the heuristic algorithm, the algorithm may learn and improve in fraud detection accuracy.

Abstract: An image analysis device includes a person detecting unit for detecting person images from image information from a surveillance camera, and acquiring both pieces of person image information as a result of the detection of person images, and pieces of attribution information about persons corresponding to the pieces of person image information, and a person narrowing down unit for performing narrowing-down of person image information with respect to the pieces of person image information and the pieces of person attribution information which are acquired by the person detecting unit, on the basis of a person narrowing down rule, to acquire person image information after the narrowing-down and attribution information about a person corresponding to the person image information.

Abstract: An image processing method, an image processing device and a computer storage medium are provided. The method includes: performing a maximum-filtering processing on an original image and obtaining a luminance channel of the image; and performing a guided-filtering processing on the obtained luminance channel, and estimating and obtaining an incident component.

Abstract: A method of creating a fiducial marker image includes setting option information about a fiducial marker, calculating size information about each of parameters of the fiducial marker on the basis of the set option information, adding identification (ID) bit information on the basis of the calculated size information to generate a cell matrix, and adding color information to the generated cell matrix to create a fiducial marker image.

Abstract: Methods, systems and computer-readable media for extracting data from a document. One method includes receiving a document in a text format and assigning a first signature to the document. The method also includes matching the first signature to a second signature of a template and extracting data a user desires to have extracted from the document, wherein instructions for locating the data are stored within the template.

Abstract: In a gradient direction calculation device, an element gradient vector calculation unit calculates two mutually perpendicular element gradient vectors with respect to a pixel of interest by using a difference in pixel values in the vicinity of the pixel of interest. A quadrant determination unit determines, based on a combination of positive/negative signs of each of the two element gradient vectors, a quadrant among the four quadrants defined by the two element gradient vectors that contains a gradient direction of the pixel of interest. A ratio comparison unit determines comparison results by comparing each of the ratios of magnitudes of the two element gradient vectors with a predetermined threshold. A gradient direction determination unit determines a gradient direction corresponding to a combination of the positive/negative signs and the comparison results.

Abstract: Techniques for generating and processing two-dimensional barcodes are described. One example method includes identifying original content to be encoded in a two-dimensional (2D) barcode structure; and generating a 2D barcode associated with the original content based on at least the 2D barcode structure and the original content, wherein the 2D barcode structure includes at least an identification field and a data field, and the identification field indicates one or more data elements in the data field.

Abstract: A method for quantitatively measuring internal defects in an as-cast steel product includes optically scanning at least a portion of a surface of the steel product with a scanning device to create a digital image thereof. The method further includes thresholding the image in a thresholding engine to isolate internal defects within the image and analyzing the thresholded image to determine an internal defect area, wherein the internal defect area includes an area of at least a portion of the thresholded image that is occupied by the internal defects. The method further includes determining an overall area of the portion of the thresholded image, calculating a fraction of the internal defect area relative to the overall area, and calculating an equivalent Mannesmann scale rating of the internal defects in the steel product based on the fraction.

Abstract: A method for database retrieval is provided. The method may include receiving a history datastore. The method may include receiving a payment, i.e., a paper check. The method may include simultaneously scanning the check into a grayscale image and black and white image. The method may include reviewing each pixel on the black and white image alone and in combination with surrounding pixels to determine an arrangement of shaded pixels. When the arrangement of shaded pixels is determined to be above a predetermined threshold of similarity to a predefined set of characters, the method may determine a subset of characters and store the subset of characters in a memory. The method may include crawling the history datastore to determine information which corresponds to the subset of characters stored in memory and retrieving the corresponding information. The method may include showing the corresponding information and the payment on a GUI.

Abstract: A restoration filter generation device that generates a restoration filter to perform restoration processing on luminance system image data that is image data related to luminance, which is generated based on image data of respective colors of multiple colors obtained by an imaging device having an optical system, includes an information acquisition device acquiring transfer function information corresponding to point image distribution in the optical system, for each color of the multiple colors, and a restoration filter generation device generating the restoration filter based on the transfer function information acquired by the information acquisition device and generating the restoration filter that performs phase correction of the luminance system image data according to the transfer function information on a single color of the multiple colors.

Abstract: In a liveness detection system, a first set of one or more parameters of a first liveness test is selected at random. The first parameter set is transmitted to a user device available to an entity, thereby causing the user device to perform the first liveness test according to the first parameter set. Results of the first liveness test performed at the user device according to the first parameter set are received form the user device. Results of a second liveness test pertaining to the entity are received. The liveness detection system determines whether the entity is a living being using the results of the liveness tests, the results of the first liveness test being so used by comparing them with the first parameter set.

Abstract: Methods, systems and processor-readable media for side window detection in near-infrared (NIR) images utilizing machine learning. An image-capturing unit can capture an image/video in a near-infrared (NIR) band via a side window of an incoming vehicle. A deformable part model can be generated utilizing a side window detection and B-frame detection in order to obtain a set of candidate side-windows. Side window detection can be performed based on a mixture of a tree model and a shared pool and can be globally optimized with dynamic programming and still-capture to detect the backseat side window boundary utilizing a B-pillar. A false alarm with respect to the deformable part model can be removed utilizing a super pixel generation and a longest-line detection unit in order to generate a refined deformable part model.

Abstract: Neural-network-based image segmentation techniques are provided herein. An input image that includes a plurality of characters can be received. Boundaries between the characters can be identified using a trained neural network. The input image can be segmented along the boundaries identified between the characters. The neural network can be trained using a training image and a training target vector. The training target vector can indicate one or more boundaries between characters in the training image. Neural-network-based segmentation can be used alone or in conjunction with other segmentation techniques to improve overall segmentation accuracy.

Abstract: A computer-implemented method includes: determining an intensity of a visual effect to be applied to a user interface element; adjusting the intensity of the visual effect based on a characteristic feature of a background area; and rendering the user interface element based on the adjusted intensity of the visual effect.

Abstract: A method and an electronic apparatus for locating the center of a pupil are provided. The method includes: obtaining a glint-free image including a pupil; generating a gradient magnitude graph and a gradient orientation graph based on the glint-free image; sifting a plurality of first pixels from the gradient magnitude graph, and finding a plurality of second pixels corresponding to the plurality of first pixels in the gradient orientation graph; taking a negative gradient orientation to each of the second pixels to generate a gradient emission graph including a plurality of emissions; defining a center of the pupil in the glint-free image based on the plurality of emissions in the gradient emission graph.

Abstract: Systems, devices, features, and methods for determining geographic features corresponding to a travel path to develop a map database, such as a navigation database, are disclosed. For example, one method comprises emitting light from a light source, such as a LIDAR device, while on the travel path. Returning light is received based on the emitted light. The returning light is used to generate data points representing an area about the travel path. The data points are filtered as a function of a return intensity value to identify a feature associated with the travel path, in which the feature is treated with a retroreflective substance.

Abstract: Neural-network-based image segmentation techniques are provided herein. An input image that includes a plurality of characters can be received. Boundaries between the characters can be identified using a trained neural network. The input image can be segmented along the boundaries identified between the characters. The neural network can be trained using a training image and a training target vector. The training target vector can indicate one or more boundaries between characters in the training image. Neural-network-based segmentation can be used alone or in conjunction with other segmentation techniques to improve overall segmentation accuracy.

Abstract: A computer-implemented system and method for controlling document image capture are provided. The method includes identifying a categorization model for categorizing image frames and configuring an image capture device, based on the identified categorization model. A flow of frames of a same document captured with the configured image capture device is received and an image representation generated for each of a plurality of frames within the flow of frames. With the identified categorization model, for each of the plurality of frames, a confidence for at least one category is assigned to the frame based on the image representation. A category is assigned to the document when a threshold confidence for one of the at least one categories is assigned. An automatic capture of an image of the document is triggered based on the assigned category.

Abstract: A method of providing a unique identifier for a manufactured part includes defining a boundary area on at least one surface of the manufactured part, recording surface properties within a portion of the boundary area, interpreting the recorded surface properties with a pattern recognition algorithm to create the unique identifier, and storing the unique identifier in a database.

Abstract: In accordance with an example embodiment a method, apparatus and computer program product are provided. The method comprise assigning weights to at least one first feature and at least one second feature. The at least one first feature may be associated with a first image and the at least one second feature may be associated with a second image. The weights are assigned based on a distance of the at least one first feature and the at least one second feature from a central portion of the corresponding one of the first image and the second image. The method further includes registering the first image and the second image based at least on the assigned weights to determine transforms between the first image and the second image. The first image and the second image may be based on the determined transform.

Abstract: There is provided an information processing apparatus including a statistical quantity extraction section calculating similarities between all of a group of multiple images of a first identification target and all of a group of multiple images of a second identification target and extracting a statistical quantity for similarity from the similarities and an identification section identifying the first identification target with the second identification target based on the statistical quantity for similarity. The present technology may be applied to a personal computer, for example.

Abstract: An information processing method comprises the steps of: inputting an input information of a multi-dimensional array; calculating an accumulated information value corresponding to a position of each element of the input information; and holding the accumulated information value in a buffer having a size of predetermined bits, wherein in the holding step, when an accumulated information value calculated in the calculating step overflows with respect to the size, a part not more than the predetermined bits of the calculated accumulated information value is held as the accumulated information value.

Abstract: A method for classifying defect images is provided. Defect images are processed through an automatic optical detection. The present invention integrates image analysis and data mining. Defects are found on the images without using human eye. The defects are classified for reducing product defect rate. Thus, the present invention effectively enhances performance on finding and classifying defects with increased consistency, correctness and reliability.

Abstract: According to one embodiment, an image processing apparatus includes following units. The correlation calculation unit calculates correlations between a first region and predetermined first basis vectors. The distance calculation unit calculates distances between the first region and second regions on a subspace generated by the second basis vectors selected from the first basis vectors. The feature quantity calculation unit calculates a feature quantity based on the correlations. The weight calculation unit calculates weights based on the distances and the feature quantity. The pixel value calculation unit calculates a weighted average of pixel values according to the weights to generate an output pixel value.

Abstract: A method for approximate pyramidal search for displacement matching is provided that includes performing a complete window-based search at a coarsest resolution level in a resolution pyramid to determine a best matching point in a destination image for each point in a source image, wherein a displacement from each point to the best matching point is determined, counting, for each displacement of the determined displacements, a number of points having the displacement, selecting displacements from the determined displacements based on the number of points counted for each displacement and a predetermined threshold, and performing a search at the next finer resolution level in the resolution pyramid to determine a best matching point in the destination image for each point in the source image, wherein the search for a best matching point for each point is limited to the selected displacements and a reduced search window around each displacement.

Abstract: Whether an obtained candidate face image is registered or not is appropriately determined. A similarity degree calculating unit calculates the degree of similarity between a candidate face image extracted by a face image extracting unit and a registration face image registered in a storage unit. An in-class variance calculating unit calculates an in-class variance of the degree of similarity of the registered person identified by a registered person identifying unit, and an inter-class variance calculating unit calculates an inter-class variance of the degree of similarity of each registered person registered in the storage unit. A variance ratio calculating unit calculates a variance ratio between the inter-class variance and the in-class variance, and on the basis of the calculated variance ratio, a registration determining unit determines whether a target face image is to be registered or not.

Abstract: A system for organizing a plurality of candidates based on the relative similarity of a first candidate with respect to the remaining plurality of candidates is disclosed. The system includes a controller in communication with a storage device configured to receive and accessibly store a generated plurality of candidate images. The controller operable to analyze each of the plurality of candidate images to determined a numeric thumbnail based on a number of identified features in each of a plurality of grid elements of an array and a sum total number of all identified features in the array, calculate a similarity score between one of the plurality of determined numeric thumbnails and each of the remaining plurality of determined numeric thumbnails; and generate a logical group image order as a function of the highest similarity score between the one of the plurality of determined numeric thumbnails and each of the remaining plurality of determined numeric thumbnails.

Abstract: Methods, and apparatus for performing methods, for classifying an image. Methods include determining a corresponding set of metrics for each region of two or more regions of a pattern of regions of an image, and classifying the image in response to at least the corresponding set of metrics for each of the two or more regions of the pattern of regions.

Abstract: A detection apparatus that detects a feature point of an image, comprising: a conversion unit configured to convert a first image into a second image; a setting unit configured to set a first target number indicating the number of feature points to be detected from the first image and to set a second target number indicating the number of feature points to be detected from the second image based on the first target number and the number of feature points that are detected from the first image; and a processing unit configured to perform processing for detecting a feature point from the first image based on the first target number and processing for detecting a feature point from the second image based on the second target number.

Abstract: Methods, systems, and articles of manufacture for annotating of an image are disclosed. These include scoring the image using a plurality of trained classifiers, wherein each of the trained classifiers corresponds to at least one of a plurality of image groups clustered based upon image similarity, and wherein each image group is associated with a set of weighted labels; selecting one or more of the image groups based upon the scoring; aggregating one or more sets of weighted labels associated with the selected one or more image groups; and annotating the image using the aggregated one or more sets of weighted labels.

Abstract: A system and method to detect similarities between images. The system and method allow comparisons between a query image and one or more catalog images in a manner that is resilient to scanning, scaling, rotating, cropping and other distortions of the query image. The system includes an image processing module that determines and/or calculates principle features of a catalog image and constructs a feature vector using one or more of the principle features. The system also includes a matching module that matches a query image to one or more catalog images. The system finds matches based on a distance measure of features present in the query image and features present in the catalog images.

Abstract: In an imaging device having an objective and a stage for holding a sample to be imaged, a method for autofocusing is presented. The method includes determining a measured focus value corresponding to at least a first of a plurality of logical image segments. Further, the method includes imaging the first logical image segment using the measured focus value. The method also includes determining a predicted focus value for a second of the plurality of logical image segments using the measured focus value and a stored focus variation parameter. In addition, the method includes imaging the second logical image segment using the predicted focus value.

Abstract: A method of processing graphical image data representing optically scanned medication-related units may include receiving image data generated responsive to disposal of the units on a tray disposed a distance from an image acquisition component, the image data including data indicative of visually observable features of the units disposed on the tray. The method further includes comparing at least two features among the visually observable features from the image data to reference data indicative of corresponding features of reference units. The reference data is selected for comparison based on an identification of the reference data as corresponding to a prescription being processed. The reference data includes data indicative of features of the reference units extracted from images captured using hardware corresponding to hardware used to generate the image data. The method further includes generating a likelihood rating for each of the at least two features based on the comparing.

Abstract: Methods and apparatuses for identifying an image based on Embedded Media Marker (EMM) identification. A hierarchal comparison including a first coarse comparison and a second refining comparison is used. The first coarse comparison compares an image with an EMM to images in a database at a low resolution. The results are fed to the second refining comparison, which conducts a comparison at a higher resolution than the first coarse comparison. By utilizing this hierarchical comparison approach, it is possible to identify the image with fewer false positives.