Abstract: Examples of the present disclosure relate to an image processing apparatus comprising a filter to convert a first image data signal into an output image data signal. The filter is configured to resample the first image data signal, having a first sample rate, by a resampling factor, such that the output image data signal has an output sample rate that is different to the first sample rate. The filter is also configured to apply a phase alteration to the first image data signal to compensate a group delay in the first image data signal.

Abstract: The present invention discloses methods and systems face recognition. Face recognition involves receiving an image/frame, detecting one or more faces in the image, detecting feature points for each of the detected faces in the image, aligning and normalizing the detected feature points, extracting feature descriptors based on the detected feature points and matching the extracted feature descriptors with a set of pre-stored images for face recognition.

Abstract: Three-dimensional (3D) measurement systems and methods are provided. The systems and methods include a 3D imager and a marker. The marker includes an adapter and a marker element, wherein the adapter is arranged to be at least one of installed, placed, and attached to a fixed object of a scanned environment and the marker element includes a coded identifier that is detectable by the 3D imager, wherein the coded identifier identifies the specific location of the fixed object within the scanned environment.

Abstract: The present disclosure relates to a method and system for reducing radiation dose in image acquisition. The method may include obtaining first image data of a subject related to a first scan of the subject. The first scan may be of a first type of scan. The method may include reconstructing a first image of the subject based on the first image data and generating a dose plan of a second scan based on the first image. The second scan may be of a second type of scan. The method may also include obtaining second image data of the subject related to the second scan of the subject. The second scan may be performed according to the dose plan.

Abstract: An image synthesizing method includes capturing a first image using a reference small aperture size; capturing a second image using a reference large aperture size; obtaining one or more reference color weights according to a corresponding pixel of the first image and adjacent pixels of the corresponding pixel of the first image and a corresponding pixel of the second image; obtaining an associated distance by looking up an association table according to the one or more reference color weights; obtaining one or more associated color weights by looking up the association table according to the associated distance and an expected aperture; and obtaining a color value of a corresponding pixel of a synthesized image, by applying weighting to the corresponding pixel of the first image and the adjacent pixels of the corresponding pixel of the first image with the one or more associated color weights.

Abstract: Embodiments described herein are directed to methods and systems for facilitating control of smoothness of transitions between images. In embodiments, a difference of color values of pixels between a foreground image and the background image are identified along a boundary associated with a location at which to paste the foreground image relative to the background image. Thereafter, recursive down sampling of a region of pixels within the boundary by a sampling factor is performed to produce a plurality of down sampled images having color difference indicators associated with each pixel of the down sampled images. Such color difference indicators indicate whether a difference of color value exists for the corresponding pixel. To effectuate a seamless transition, the color difference indicators are normalized in association with each recursively down sampled image.

Abstract: A method for determining population density of a defined space from multi-camera sourced imagery includes loading a set of images acquired from multiple different cameras positioned about the defined space, locating different individuals within each of the images and computing a population distribution of the located different individuals in respect to different locations of the defined space. The method additionally includes submitting each of the images to a convolutional neural network as training data, each in association with a correspondingly computed population distribution. Subsequent to the submission, contemporaneous imagery from the different cameras is acquired in real time and submitted to the neural network, in response to which, a predicted population distribution for the defined space is received from the neural network. Finally, a message is displayed that includes information correlating at least a portion of the population distribution with a specific location of the defined space.

Abstract: A method of processing a digital image, the method comprising receiving a digital image, modifying each row of pixel colour values and then each column of modified pixel colour values or vice versa, represented as an array X of pixel or modified pixel colour values x(i), by calculating each value y(i) of an array Y as a function at least of an exponentially weighted moving average a(i) of the array X, calculated in ascending order of the array X value indices, and an exponentially weighted moving average b(i) of the array X, calculated in descending order of the array X value indices, or an exponentially weighted moving average b?(j) of an array X? containing the values of the array X in reverse order, calculated in ascending order of the array X? value indices, where i, j are the array value indices, wherein 0?i<N, j=N?1?i, N is the array size, with replacement of x(i) with y(i).

Abstract: According to a first aspect of the present disclosure, a fingerprint sensor module is provided, comprising: an assembly comprising a substrate and a fingerprint sensor mounted on one side of the substrate; wherein the fingerprint sensor comprises a set of sensor elements and a measurement unit; and wherein the measurement unit is configured to concurrently measure capacitances on subsets of the set of sensor elements. According to a second aspect of the present disclosure, a corresponding method of producing a fingerprint sensor module is conceived.

Abstract: Disclosed are systems and methods for automatic selection of canonical digital images from a large corpus of digital images, such as the corpus of digital images available on the web, for an entity, such as and without limitation a person, a point of interest, object, etc. The automated, unsupervised approach for selecting a diverse set of high quality, canonical digital images, is well suited for processing a large corpus of digital images. A set of canonical digital images identified for an entity can be retrieved in response to a digital image request for digital images depicting the entity.

Abstract: An image operation method and system for obtaining an eye's gazing direction are provided. The method and system employ multiple extraction stages for extracting eye-tracking features. An eye frame is divided into sub-frames, which are then sequentially temporarily stored in a storage unit. Launch features of sub frames are sequentially extracted from the sub frames by a first feature extraction stage, where a data of a former sub-frame is extracted before a data of a latter sub-frame is needed to be stored. Next, the remaining feature extraction stages apply a superposition operation on the launch features to obtain terminal features, which are then computed to obtain an eye's gazing direction.

Abstract: Systems, methods and apparatus for image processing for reconstructing a super resolution (SR) image from multispectral (MS) images. A processor to iteratively, fuse a MS image with an associated PAN image of the scene. Each iteration includes using a gradient descent (GD) approach with a learned forward operator, to generate an intermediate high-resolution multispectral (IHRMS) image with an increased spatial resolution and a smaller error to the DSRMS image compared to the stored MS image. Project the IHRMS image using a trained convolutional neural network (CNN) to obtain an estimated synthesized high-resolution multispectral (ESHRMS) image, for a first iteration. Use the ESHRMS image and the PAN image, as an input to the GD approach for following iterations. The updated IHRMS image is an input to another trained CNN for the following iterations. After predetermined number of iterations, output the fused high-spatial and high-spectral resolution MS image.

Abstract: Disclosed is a device for optical sensing, comprising: a display comprising a transparent substrate and a plurality of light emitters disposed above the transparent substrate; a transparent cover layer disposed above the display, wherein a top surface of the transparent cover layer provides an input surface for sensing an input object; and, an angled filter disposed below the transparent substrate of the display, wherein the angled filter is configured to allow light within a tolerance angle of an acceptance angle to pass through the angled filter, wherein the acceptance angle is centered around a non-zero angle relative to a normal of the input surface.

Abstract: An image processing method of generating a range image is provided. The method includes a step of detecting a distance to the object as a measured distance, by a distance measurement unit; a step of performing, by an image processing unit, integration of the distance with a matching evaluation value of a pixel in a stereogram corresponding to a location on the object of which the distance is detected by the distance measurement unit, among a plurality of pixels in the stereogram each including a corresponding matching evaluation value; and a step of generating a range image based on a result of the integration. The generating step is performed after the integration.

Abstract: Access to items stored within an inventory location of a facility may be controlled using physical access control mechanisms. A user within a facility is detected by sensors, such as imaging sensors. Context data for the user is generated based on the sensor data. The context data includes permission data indicative of portions of the inventory location that are accessible or inaccessible to the user. In addition, a predicted path of the user may also be determined based on historical data of the user or other users of the facility. Using the permission data and the predicted path of the user, configuration data may be generated to specify the level of access control to be applied to the different portions of the inventory location. The configuration data is sent to access control mechanisms of the inventory location to prevent or allow access to such portions of the inventory location.

Abstract: Embodiments of this application disclose an image splicing method and apparatus, a terminal, and a storage medium thereof. The image splicing method includes determining a primary position parameter of a current image according to a first overlapped region in the current image; and projecting the current image to a projection canvas according to the primary position parameter to obtain an initial spliced image, the initial spliced image being obtained by splicing the current image and the neighboring image. The method further includes selecting a partially overlapped region from a second overlapped region of the initial spliced image; calculating a partial position parameter of a partial image region corresponding to the partially overlapped region in the current image; and projecting the current image to the projection canvas again according to the primary position parameter and the partial position parameter, to obtain a target spliced image.

Abstract: A face clustering system for video face clustering in a video sequence, the system including an inherent supervision summarization device configured to collect group-level supervision and instance level supervision within a same chunklet based on a user input of face images for a person, a discriminative projection learning device configured to embed group constraints of the group-level supervision into a transformed space, and configured to generate an embedding space from the original image feature space, and a clustering device, in the embedding space, configured to execute pair-wise based clustering to cluster the video images into different clusters with the instance level supervision collected by the inherent supervision summarization device.

Abstract: A display panel and a display device are disclosed. The display panel includes a display-side substrate, and a display array layer, a lens layer and an image array layer, which are sequentially provided at a side of the display-side substrate. The display array layer includes a plurality of display pixels arranged in an array; and the image array layer includes a plurality of image pixels arranged in an array, and is configured to form an image with light being reflected from a display side and passing through the lens layer.

Abstract: A fingerprint identification device includes a substrate, at least two electrode areas, at least one dedicated sensing signal line, plural electrode selection switch groups, and plural signal lines. Each electrode area has plural electrodes. The signal lines are divided into plural first directional signal lines and plural second directional signal lines. The first directional signal lines are perpendicular to the second directional signal lines. The plural electrode selection switch groups sequentially or dynamically select at least one electrode as a sensing electrode block in each electrode area. The plural electrode selection switch groups configure the electrodes surrounding the sensing electrode block as at least two corresponding deflection electrode blocks. Each sensing electrode block is corresponding to at least two deflection electrode blocks. Each deflection electrode block has plural electrodes.

Abstract: Tools, strategies, and techniques are provided for evaluating the identities of different entities to protect business enterprises, consumers, and other entities from fraud by combining biometric activity data with facial recognition data for end users. Risks associated with various entities can be analyzed and assessed based on a combination of user liveliness check data, facial image data, social network data, and/or professional network data, among other data sources. In various embodiments, the risk assessment may include calculating an authorization score or authenticity score based on different portions or combinations of the collected and processed data.