Abstract: Systems and methods for document analysis. An image containing at least one document is received at a pre-processing stage and the image is analyzed for image quality. If the image quality is insufficient for further processing, this is adjusted until the image is suitable for further processing. After the image quality adjustment, the image is then passed to an initial processing stage. At the initial processing stage, the boundaries of one or more documents within the image are determined. In addition, the orientation of the image may be adjusted and the type of document(s) within the image is determined. From the initial processing stage, the adjusted image is then passed to a data extraction stage. At this stage, clusters of data within the document are determined and bounding boxes are placed around the clusters. Data regarding each of the clusters of data is then gathered.

Abstract: A method of the disclosure includes receiving, by a processing device, a document image, dividing the document image into a plurality of patches and determining, for each patch, whether the patch is monochromatic or polychromatic. It further includes clusterizing a plurality of monochromatic patches into a plurality of clusters within a color space, wherein each cluster corresponds to a color layer of a plurality of color layers of the document image, and segmenting each polychromatic patch into a corresponding plurality of monochromatic segments. The method also includes, for each polychromatic patch, associating each monochromatic segment of the corresponding plurality of monochromatic segments with a cluster of the plurality of clusters, and utilizing the plurality of clusters for performing an information extraction task on the document image.

Abstract: ROI (Region of Interest) detection is an important step in extracting relevant information from a document image. Such images are very high-resolution images in nature and size of images is in order of megabytes, which makes text detection pipeline very slow. Traditional methods detect and extract ROI from images, but these work only for specific image types. Other approaches include deep learning (DL) based methods for ROI detect which need intensive training and require high end computing infrastructure/resources with graphical processing unit (GPU) capabilities. Systems and methods of the present disclosure perform ROI extraction by partitioning input image into parts based on its visual perception and then classify the image in first or second category. Region of interest is extracted from a resized image based on the classification by applying image processing techniques. Further, the system determines whether the input image is a pre-cropped image or a normal scanned image.

Abstract: A method, apparatus and computer program product to provide machine learning-assisted detection of objects of interest in live cell-based assays, where the objects of interest are larger than cells used in the assay. The technique herein comprises receiving image data that has been captured from a set of imaging devices, such as immune monitoring analyzer machines. Representative image data is an enzyme-linked immune absorbent spot (ELISPOT) assay captured from an ELISPOT analyzer. For each set of image data, the image data is then processed using, for example, one of: (a) a first pre-trained model; and (b) a set of one or more detection algorithms, to generate training data comprising a set of labels for the image data. A model, e.g., a deep neural network (DNN), is then trained using the set of labels. Following training, the model is provided for detection of the objects of interest.

Abstract: An image coloring method includes: acquiring first color a priori information about an image-to-be-colored; transforming the first color a priori information to obtain second color a priori information aligned with the image-to-be-colored; downsampling the image-to-be-colored to obtain a first image feature; performing modulation coloring processing on the first image feature based on the second color a priori information to obtain a second image feature; and upsampling the second image feature based on the second color a priori information to obtain a first colored image, where the first colored image is aligned with the image-to-be-colored.

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: A path planning system includes an image-capturing device, a point-cloud map-retrieving device, and a processing device. The image-capturing device captures a first and a second camera road image. The point-cloud map-retrieving device retrieves distance data points to create a road distance point-cloud map. The processing device receives the road distance point-cloud map and the first and second camera road images, calibrates and fuses those to generate a road camera point-cloud fusion map, and then determines the road-line information of the second camera road image to generate a road-segmented map. The road-segmented map and the road camera point-cloud fusion map are fused. The distance data of the road-segmented map are obtained according to distance data points. A front driving path for the target road is planned according to the distance data.

Abstract: A system and method identifying an object, such as a transparent object, to be picked up by a robot from a bin of objects. The method includes obtaining a 2D red-green-blue (RGB) color image and a 2D depth map image of the objects using a 3D camera, where pixels in the depth map image are assigned a value identifying the distance from the camera to the objects. The method generates a segmentation image of the objects using a deep learning mask R-CNN (convolutional neural network) that performs an image segmentation process that extracts features from the RGB image and assigns a label to the pixels so that objects in the segmentation image have the same label. The method then identifies a location for picking up the object using the segmentation image and the depth map image.

Abstract: Apparatuses, systems, and techniques to interpolate one or more intermediate images from two or more images is disclosed. In at least one embodiment, a processor includes one or more circuits to interpolate one or more intermediate images from two or more images based, at least in part, on one or more inconsistent flow vectors corresponding to the two or more images.

Abstract: A ground surface estimation method include: performing first estimation in which the continuous region having a largest number of the grids among the continuous regions is estimated as a ground surface; and performing second estimation including: calculating an average altitude value of the representative point of the grids in the non-adjacent continuous region for each of the non-adjacent continuous regions; calculating an average altitude value of the representative point of the grids in the predetermined range of the continuous region estimated as the ground surface; and estimating that a non-adjacent continuous region as the ground surface when a difference between the average altitude value of the representative point of the grids in the non-adjacent continuous region and the average altitude value of the representative point of the grids in a predetermined range of the continuous region estimated as the ground surface is equal to or less than a threshold.

Abstract: To provide a technique for estimating, using an image photographed by a camera with a low sampling frequency, information on a position and a size of a pupil or an iris in time units that are finer than the actual sampling frequency.

Abstract: There are provided an imaging data generation apparatus, an imaging data generation method, and a program for enriching data accumulated as a life log. A sensing data reception section (40) receives multiple captured images successively. A life log data generation section (42) generates an environmental map based on the multiple captured images. The life log data generation section (42) generates imaging data indicative of an imaging position or a subject of the captured image, the imaging data being associated with the environmental map.

Abstract: Disclosed are example embodiments of systems and methods for virtual try-on of articles of clothing. An example method of virtual try-on of articles of clothing includes selecting a garment from a pre-existing database. The method also includes loading a photo of a source model wearing the selected garment. Additionally, the method includes generating a semantic segmentation of the model image. The method also includes extracting the selected garment from the photo of the model. Additionally, the method includes determining a correspondence between a target model and the source model by performing a feature point detection and description of the target model and the source model, and performing feature matching and correspondence validation. The method also includes performing garment warping and alignment of the extracted garment. Additionally, the method includes overlaying and rendering the garment.

Abstract: An image processing apparatus includes circuitry to determine a type of a document read by a scanner, set a top-bottom determination method based on the type of the document, and determine a top-bottom orientation of a target image by the top-bottom determination method. The target image is obtained by reading the document with the scanner.

Abstract: The present disclosure discloses an image data processing system, and discloses an image data processing system for a vehicle, which compensates image data by reflecting an ambient illumination.

Abstract: A system and method for identifying a box to be picked up by a robot from a stack of boxes. The method includes obtaining a 2D red-green-blue (RGB) color image of the boxes and a 2D depth map image of the boxes using a 3D camera, where pixels in the depth map image are assigned a value identifying the distance from the camera to the boxes. The method generates a segmentation image of the boxes by performing an image segmentation process that extracts features from the RGB image and the depth map image, combines the extracted features in the images and assigns a label to the pixels in a features image so that each box in the segmentation image has the same label. The method then identifies a location for picking up the box using the segmentation image.

Abstract: Analysis of edge closures of metal surface particles based on a graph structure.

Abstract: A non-transitory computer-readable medium includes program code that is stored thereon. The program code is executable by one or more processing devices for performing operations including generating, using a model, a learned image representation of a target image. The operations further include generating, using a text embedding model, a text embedding of a text query. The text embedding and the learned image representation of the target image are in a same embedding space. Additionally, the operations include convolving the learned image representation of the target image with the text embedding of the text query. Moreover, the operations include generating an object-segmented image based on the convolving of the learned image representation of the target image with the text embedding.

Abstract: A method of video search in an electronic device is provided. The method includes extracting a plurality of visual features vectors comprising visual features from a plurality of videos stored in a video database, wherein each visual feature corresponds to a pre-defined moment, generating a temporal map of the plurality of visual feature vectors, generating at least one video tag and at least one time stamp associated with the visual feature vector, storing the at least one video tag, the visual feature vectors and the at least one time stamp for each visual feature in a vector database, receiving a search query from a user for a specific moment in a plurality of videos in the electronic device, running the search query on the vector database, and displaying visual features associated with the specific moments from the plurality of videos.

Abstract: Disclosed is a hand-held optical apparatus and method for using the apparatus to activate and detect optical emissive materials as part of a safety interlock system. Typically, the hand-held optical apparatus will include one or more light sources capable of emitting at least one wavelength of light towards an optical emissive material, a light detector capable of detecting a response from the optical emissive material, and control circuitry configured to cause at least one of the one or more light sources to emit the at least one wavelength at a power density less than a predetermined threshold, receive a signal from the light detector representing a detected response, and repeat until the microprocessor determines the detected response matches an expected response.

Abstract: A tactile vibration signals is satisfactorily transmitted. A transmission signal for each block including a plurality of frames for an audio signal is sequentially transmitted to a receiving side via a predetermined transmission line. The transmission signal includes a tactile vibration signal of a predetermined number of channels. For example, the tactile vibration signal is generated on the basis of a media signal associated with the audio signal. For example, configuration information of the tactile vibration signal of the predetermined number of channels is added to the transmission signal. For example, the configuration information is added by use of a predetermined bit area of a channel status configured for each block.

Abstract: Systems, devices, methods, and computer processing products for automatically checking for errors in segmentation (contouring) using heuristic and/or statistical evaluation methods.

Abstract: Storage (24) stores therein a teacher model (54) that is a target image (50) with a teacher annotation (52), which specifies the target image (50), assigned thereto. An inferring section (32) assigns based on the teacher model (54) an inferred annotation (82) to an inspection image (80) belonging to the same category to which the target image (50) belongs. The inferred annotation (82) is a result of inference from the inspection image (80) based on the teacher model (54). An aiding section (34) aids a human to determine whether or not the inferred annotation (82) specifies the inspection image (80). A correcting section (36) generates a corrected model (86) in a manner to add a corrected annotation (84) to the inferred annotation (82) so that the inspection image (80) is specified.

Abstract: An image reading apparatus includes a transparent member having a placement surface on which a document is to be placed, a reading unit configured to read an image of the document placed on the transparent member via the transparent member, and a reading mode in which an image of a document, placed in a holding member with a transparent portion, is read. The document to be read is placed in the holding member so as to be visible via the transparent portion and the holding member is placed on the placement surface with the transparent portion of the holding member in contact with the placement surface. A processor detects an edge in an image acquired by the reading unit in the reading mode, and to extract an image surrounded by an edge detected in an area surrounded by an edge corresponding to the holding member in the reading mode.

Abstract: An important aspect of augmented reality (AR) is that digital information, such as rendered images of AR scenes and objects, are integrated with the user's view of the real world in real time. However, transmitting large images over the network may negatively impact the real time aspect of the AR experience. Methods and systems for dynamic image compression based on perceived viewing distance are described herein. In some implementations, image compression of streaming AR content is based on real world distances of AR objects relative to a user or client device. In some implementations, image compression of streaming AR content is based on relative depth information. In some implementations, image compression of streaming AR content is based on a type of information or content associated with an AR object. The dynamic image compression based on perceived viewing distance provided by the systems and methods disclosed herein may also be applied to video codecs.

Abstract: Technologies for performing random sparse lifting and Procrustean orthogonal sparse hashing using column read-enabled memory include a device that has a memory that is column addressable and circuitry connected to the memory. The circuitry is configured to add a set of input data vectors to the memory as a set of binary dimensionally expanded vectors, including multiplying each input data vector with a projection matrix. The circuitry is also configured to produce a search hash code from a search data vector, including multiplying the search data vector with the projection matrix. Further, the circuitry is configured to determine a Hamming distance between the search hash code and each of the binary dimensionally expanded vectors.

Abstract: A system and a method for a crowd surveillance device comprising a multi-sensor system connected to a processing device, wherein the processing device comprises an image fusion module for receiving images from the multi-sensor system, transforming and fusing images into a fused image; an image analytic module for extracting each individual target and identifying any conceal object on the individual target, an alert triggering module for triggering an alert in the event a conceal object on the individual target is identified.

Abstract: An imaging device for image generation of a specimen is disclosed. Layers of images may be captured by an optical system and then compiled to create an integrated image. Each layer may include a different focal point. A consolidated image may then be created by combining one or more integrated images.

Abstract: An image processing method, an image processing device, an electronic apparatus, and a non-transitory computer-readable storage medium are provided. The image processing method includes: obtaining an original image; performing slicing processing on the original image to obtain multiple slice images of the original image; respectively processing the slice images through a first binarization model to obtain multiple slice binary images respectively corresponding to the slice images; performing stitching processing on the slice binary images to obtain a first binary image; processing the first binary image to obtain a pixel circumscribed contour image; processing the original image through a second binarization model to obtain a second binary image; synthesizing the second binary image and the first binary image according to positions of multiple circumscribed contour pixels in the pixel circumscribed contour image to obtain a synthetic image.

Abstract: Embodiments of the disclosure provide an image processing method and apparatus, a computer-readable medium, and an electronic device. The image processing method includes: extracting a feature map of a target image; dividing the feature map into target regions; determining weights of the target regions according to feature vectors of the target regions; and generating a feature vector of the target image according to the weights of the target regions and the feature vectors of the target regions.

Abstract: A device and a corresponding system are disclosed. The device may comprise a display. Additionally, the device and/or system may be operable to detect stale images. Further, the stale images may be detected in devices and/or systems where incoming images—such as from an imager—are received at a frame rate different than that of the display. A controller may detect the stale images by assigning hash values to images of each frame displayed by the display; storing novel hash values in a memory; and maintaining a counter. The counter may be maintained such that assigning a repeat hash value increments the counter by one and assigning novel hash values resets the counter to zero. Further, the stale images may be determined based, at least in part, on the counter value.

Abstract: The present application relates to an image processing method and system. The method includes: determining an enhanced image of a target object of an input image based on a segmentation algorithm, where the enhanced image of the target object comprises an image in which each pixel classified as the target object is displayed in an enhanced manner; and determining a positioning image of the target object by applying an integral image algorithm to the enhanced image of the target object.

Abstract: Techniques are provided for determining a cell count within a whole slide pathology image. The image is segmented using a global threshold value to define a tissue area. A plurality of patches comprising the tissue area are selected. Stain intensity vectors are determined within the plurality of patches to generate a stain intensity image. The stain intensity image is iteratively segmented to generate a cell mask using a local threshold value that is and gradually reduced after each iteration. A chamfer distance transform is applied to the cell mask to generate a distance map. Cell seeds are determined on the distance map. Cell segments are determined using a watershed transformation, and a whole cell count is calculated for the plurality of patches based on the cell segments. A client device may be configured for real-time cell counting based on the whole cell count.

Abstract: The constrained watershed boundary (CWB), defined as a polygon containing all the flow direction grid cells with a surface flow distance less than a user prescribed threshold uses an algorithm that builds upon the HSM algorithm proposed and augments the data structure with a flow distance grid calculated directly from the original flow direction grid.

Abstract: A method for associating a link to web content with a multimedia content element are provided. The method includes identifying at least one multimedia content element in a web-page; generating, by a signature generator system, a signature for the at least one multimedia content element, wherein the signature generator system includes a plurality of computational cores enabled to receive the multimedia content element and to generate a signature for at least a portion of the multimedia content element, each computational core having properties that are at least partly statistically independent of the other computational cores; matching the generated signature to signatures of web content existing on at least one web server to determine matching web content; determining a link to the matching web content; and modifying the at least one multimedia content by adding the link.

Abstract: In some examples, a smartphone or tablet includes a device able to generate a digital identifier of a copy that includes at least one print image. The device includes at least one optoelectronic detection device that detects the at least one print image and creates a representation that includes a multiplicity of pixels. The device further includes a unit that evaluates brightness intensities of the pixels, that segments the representation into multiple fields that each are composed of pixels of the representation, and that provides each of these fields with a piece of position information. The unit also ascertains, in each of these fields of adjoining pixels, a difference in their respective brightness intensities, and displays the differences as a frequency distribution. A display device further displays the digital identifier of the respective copy of the relevant printed product in the form of a graphical and/or alphanumerical display.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of receiving one or more digital images; identifying a foreground of the one or more digital images; analyzing the foreground of the one or more digital images to identify a skin region in the foreground of the one or more digital images; when the skin region is identified, clustering a non-skin remainder of the foreground of the one or more digital images into one or more clusters; extracting one or more patches of the one or more digital images from the one or more clusters of the foreground of the one or more digital images; determining one or more scores for the one or more patches of the one or more digital images; and coordinating displaying a patch of the one or more patches on an electronic display based on the one or more scores for the one or more patches. Other embodiments are disclosed herein.

Abstract: Embodiments of the invention provide a system, media, and method for deep learning applications in physical design verification. Generally, the approach includes maintaining a pattern library for use in training machine learning model(s). The pattern library being generated adaptively and supplemented with new patterns after review of new patterns. In some embodiments, multiple types of information may be included in the pattern library, including validation data, and parameter and anchoring data used to generate the patterns. In some embodiments, the machine learning processes are combined with traditional design rule analysis. The patterns being generated and adapted using a lossless process that encodes the information of a corresponding area of a circuit layout.

Abstract: A commodity sales data processing apparatus includes an image processor and a controller. The image processor captures an image including a symbol. The symbol includes discount information relating to a discount on a price of a commodity. The controller acquires commodity information that uniquely specifies the commodity. The controller extracts a region from the image captured by the camera. The region includes the symbol. The controller transmits, to a server, an image of the region extracted by the controller. The controller acquires, from the server, the discount information based on the image transmitted to the server. The controller registers the commodity information acquired by the controller and a discounted price of the commodity based on the discount information acquired by the controller in association with each other.

Abstract: Embodiments may: select a set of training images; extract a first set of features from each training image of the set of training images to generate a first feature tensor for each training image; extract a second set of features from each training image to generate a second feature tensor for each training image; reduce a dimensionality of each first feature tensor to generate a first modified feature tensor for each training image; reduce a dimensionality of each second feature tensor to generate a second modified feature tensor for each training image; construct a first generative model representing the first set of features and a second generative model representing the second set of features of the set of training images; identify a first candidate image; and apply a regression algorithm to the first candidate image and each of the first generative model and the second generative model to determine whether the first candidate image is similar to the set of training images.

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 for modeling a roof of a structure comprising a first database, a second database and a processor in communication with the first database and the second database. The processor selects one or more images and the respective metadata thereof from the first database based on a received a geospatial region of interest. The processor generates two-dimensional line segment geometries in pixel space based on two-dimensional outputs generated by a neural network in pixel space of at least one roof structure present in the selected one or more images. The processor classifies the generated two-dimensional line segment geometries into at least one contour graph based on three-dimensional data received from the second database and generates a three-dimensional representation of the at least one roof structure based on the at least one contour graph and the received three-dimensional data.

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices for autonomous vehicle operation are provided. For example, a computing system can receive object data that includes portions of sensor data. The computing system can determine, in a first stage of a multiple stage classification using hardware components, one or more first stage characteristics of the portions of sensor data based on a first machine-learned model. In a second stage of the multiple stage classification, the computing system can determine second stage characteristics of the portions of sensor data based on a second machine-learned model. The computing system can generate an object output based on the first stage characteristics and the second stage characteristics. The object output can include indications associated with detection of objects in the portions of sensor data.

Abstract: A method of reduce the impact of noise on a depth image produced using a Time Of Flight (TOF) camera uses an infrared image produced from one or more phase-specific images captured by the TOF camera to determine whether to move pixels in the depth image from one phase section to another.

Abstract: A technique for combining first and second images respectively depicting first and second subject matter to facilitate virtual presentation. The first image is processed to identify portions or regions of the first subject matter and determine an estimated depth location of each portion or region. A composite image is generated that depicts the second subject matter overlayed, inserted or otherwise combined with the first subject matter. One or more of the portions or regions of the first subject matter are added, removed, enhanced or modified in the composite image in order to generate a realistic appearance of the first subject matter combined with the second subject matter. The composite image is caused to be displayed as a virtual presentation.

Abstract: An example apparatus for generating synthesized images includes a receiver to receive a frame, a mask and external images. The apparatus also includes a foreground augmenter to generate augmented foregrounds in the frame based on the mask. The apparatus includes a background augmenter to generate augmented backgrounds based on the frame, the mask, and the external images. The apparatus also further includes an image synthesizer to generate a synthesized image based on the generated augmented foregrounds and the augmented backgrounds.

Abstract: An object is to improve character recognition accuracy of handwritten characters, originally a single continuous character string, described discontinuously. An image area corresponding to a handwritten character is separated from a document image obtained by scanning a document and a character block including characters having the same baseline is extracted. Then, in a case where a plurality of character blocks is extracted from the first image area, a single character block is generated by combining character blocks based on a position relationship of the plurality of character blocks.

Abstract: A method, a video processing apparatus and computer-readable program medium for video process is disclosed. A method of video processing includes storing, during a conversion between a current block of video and a bitstream representation of the current block, affine model parameters for the current block; and performing the conversion using the affine model parameters, wherein the affine model parameters are derived at least from motion vectors of control points of the current block.

Abstract: The present application provides a method for a WiFi module and system of the same. The method including: determining whether a specific process is a high-power consumption event; and when the specific process is determined as the high-power consumption event, performing a time-divisional operation upon the specific process. The present application further provides another method for a WiFi module, including: determining whether a specific process is a high-power consumption event; and when the specific process is determined as the high-power consumption event, estimating a first power consumption request information and transmitting the information to a control module of a local end; and receiving a first response corresponding to the first power consumption request information from the control module.

Abstract: A mechanical arm calibration system and a mechanical arm calibration method are provided. The method includes: locating a position of an end point of a mechanical arm in a three-dimensional space to calculate an actual motion trajectory of the end point when the mechanical arm is operating; retrieving link parameters of the mechanical arm, randomly generating sets of particles including compensation amounts for the link parameters through particle swarm optimization (PSO), importing the compensation amounts of each of the sets of particles into forward kinematics after addition of the corresponding link parameters, to calculate an adaptive motion trajectory of the end point; calculating position errors between the adaptive motion trajectory and the actual motion trajectory of each of the sets of particles for a fitness value of the PSO to estimate a group best position; and updating the link parameters by the compensation amounts corresponding to the group best position.