Abstract: The invention provides a method for depth estimation in image or video obtained from a distorting medium. In the method, a pixel blurriness map is calculated. A rough depth map is then determined from the pixel blurriness map while assuming depth in a small local patch is uniform. The rough depth map is then refined. The method can be implemented in imaging systems, such as cameras or imaging processing computers, and the distorting medium can be an underwater medium, haze, fog, low lighting, or a sandstorm, for example. Preferred embodiments determined the blurriness map by calculating a difference between an original image and multi-scale Gaussian-filtered images to estimate the pixel blurriness map.

Abstract: A people-flow analysis system includes an image source, a computing device, and a host. The image source captures a first image and a second image. The computing device is connected to the image source. The computing device identifies the first image according to a data set to generate a first detecting image. The first detecting image has a position box corresponding to a pedestrian in the first image. The computing device generates a tracking image according to the data set and a difference between the first detecting image and the second image. The tracking image has another position box corresponding to a pedestrian in the second image. The host is connected to the computing device and generates a people-flow list according to the first detecting image and the tracking image.

Abstract: A method for determining optimized deep learning architecture includes receiving a plurality of training images and a plurality of real time images corresponding to a subject. The method further includes receiving, by a medical practitioner, a plurality of learning parameters comprising a plurality of filter classes and a plurality of architecture parameters. The method also includes determining a deep learning model based on the plurality of learning parameters and the plurality of training images, wherein the deep learning model comprises a plurality of reusable filters. The method further includes determining a health condition of the subject based on the plurality of real time images and the deep learning model. The method also includes providing the health condition of the subject to the medical practitioner.

Abstract: A computer-implemented method for detecting landmark pairs in a pair of images is provided. The method includes receiving a pair of images, sampling the pair of images to generate reduced-resolution pairs of images, identifying features in the reduced-resolution pairs of images, matching the features in the image pairs, using the matched features in an increased resolution pair of images as guides for feature matching, and through iteratively guiding feature matching, identifying landmarks in the full-resolution pair of images.

Abstract: A system, a method, and a computer program for modelling a subsurface region of the earth for hydrocarbon exploration, development, or production, including receiving a seismic prestack dataset, determining one or more multiparameter attributes on a sparse grid based on the seismic prestack dataset, associating the one or more multiparameter attributes with color image pixels, encoding the associated one or more multiparameter attributes to generate a low-resolution colored image, inpainting the low-resolution colored image by a deep neural network to build a high-resolution colored image, and decoloring the high-resolution image.

Abstract: A vehicle, system for operating a vehicle and method of navigating a vehicle. The system includes a sensor and a multi-layer convolutional neural network. The sensor generates an image indicative of a road scene of the vehicle. The multi-layer convolutional neural network generates a plurality of feature maps from the image via a first processing pathway, projects at least one of the plurality of feature maps onto a defined plane relative to a defined coordinate system of the road scene to obtain at least one projected feature map, applies a convolution to the at least one projected feature map in a second processing pathway to obtain a final feature map, and determines lane information from the final feature map. A control system adjusts operation of the vehicle using the lane information.

Abstract: The present invention relates to a method of generating an overhead view image of an area. More particularly, the present invention relates to a method of generating a contextual multi-image based overhead view image of an area using ground map data and field of view image data. Various embodiments of the present technology can include methods, systems and non-transitory computer readable media and computer programs configured to receive a plurality of images of the geographical area, determine a ground map of the geographical area, divide the ground map into a plurality of sampling points of the geographical area; and determine a color for each of the plurality of sampling points, wherein the color of each of the sampling points is determined by determining a correlation between the sampling points of the geographical area and color of the sampling points captured in at least one of the plurality of images.

Abstract: Disclosed is an electronic device including a display configured to display an image, a sensing unit configured to sense biometric information of a user, and a controller configured to analyze the image to acquire image information and configured to provide user information based on the acquired image information and the sensed biometric information.

Abstract: A method of detecting an edge within digitized images, said method comprising steps of: (a) obtaining said image in a digital form; (b) building a 3D graph of intensity distribution within said image; (c) finding Regions of Interest ROI in the image and subtracting out the background; (d) establishing edge lines within said image; establishing a resultant edge line for each ROI by averaging or maximizing the set of independently obtained edge lines corresponding to said plurality of criteria but that differ from each other by a margin increasing with a predetermined increment; and (f) generating at least one report presenting the quantitative and/or qualitative parameters in a form of accurate quantitative measurements and qualitative inferences regarding medical and general diagnosis of the images and patients utilizing one or more output modules.

Abstract: It is possible to calculate transformation parameters used for image combining with a small error and to reduce a distortion that appears in a combined image The image processing apparatus includes: a feature point extraction unit configured to extract feature points corresponding to each other between both images from each of a first image and a second image, which are images obtained by capturing a paper document and whose captured ranges are different from each other; an edge extraction unit configured to extract edges corresponding to each other between both images from each of the images; a vanishing point detection unit configured to detect a vanishing point of a plane to which the paper document belongs from each of the images; a transformation parameter derivation unit configured to derive transformation parameters for image combining by using coordinates corresponding to intersections of straight lines connecting the feature points and the vanishing point, and the edges; and an image combining unit c

Abstract: A method for estimating a plurality of camera, comprising using at least one processor executing a code for: extracting a plurality of image features of a plurality of landmarks from a plurality of images captured by at least one camera from at least one pose, the plurality of landmarks calibrated with respect to a certain coordinate system; identifying among the plurality of image features at least one image feature documented in at least some of the images; producing scale values of at least one common image feature by analyzing the at least some of the images; determining a plurality of estimated poses of the at least one camera with respect to the certain coordinate system by using the scale values in calculating a minimal re-projection error between the plurality of image features and a plurality of predicted image features; and outputting the plurality of estimated poses.

Abstract: A scanned image authentication system employing at least one image authentication station which is unable to process scanned images which do not belong to at least one individual scanned image category, the system comprising a gateway image processor operative for on-line filtering of an incoming scanned image to determine whether or not the incoming scanned image belongs to the scanned image category, and a computer-implemented interface operative to transmit each individual scanned image to the at least one image authentication station only if the gateway image processor has determined that the individual scanned image belongs to the at least one individual scanned image category.

Abstract: A method of determining a summation of pixel characteristics for a rectangular region of a digital image includes determining if a base address for a data element in an integral image buffer is aligned for an SIMD operation by a processor embedded in an electronic assembly configured to perform Haar-like feature calculations. The data element represents a corner of the rectangular region of an integral image. The integral image is a representation of the digital image. The integral image is formed by data elements stored in the integral image buffer. The data element is loaded from the integral image buffer to the processor when the base address is aligned for the SIMD operation. An offset data element of an offset integral image is loaded from an offset integral buffer when the base address is non-aligned for the SIMD operation. The offset data element represents the corner of the rectangular region.

Abstract: When reviewing digital pathology tissue specimens, multiple slides may be created from thin, sequential slices of tissue. These slices may then be prepared with various stains and digitized to generate a Whole Slide Image (WSI). Review of multiple WSIs is challenging because of the lack of homogeneity across the images. In embodiments, to facilitate review, WSIs are aligned with a multi-resolution registration algorithm, normalized for improved processing, annotated by an expert user, and divided into image patches. The image patches may be used to train a Machine Learning model to identify features useful for detection and classification of regions of interest (ROIs) in images. The trained model may be applied to other images to detect and classify ROIs in the other images, which can aid in navigating the WSIs. When the resulting ROIs are presented to the user, the user may easily navigate and provide feedback through a display layer.

Abstract: In implementations of grid layout determination from a document image, a computing device receives a document image of a document that includes document content. The computing device implements a grid layout system that can determine feature elements of the document content in the document, and generate a node tree of bounded elements that represent relationships of the feature elements in the document, where each of the bounded elements is considered in the determination of the grid layout. The grid layout system can generate a containment model that includes the node tree of the bounded elements. The grid layout system can then determine a column layout of the columns in the document based on the containment model, which includes calculating a quantity of the columns, and also determine a row layout of the rows in the document based on the containment model, which includes calculating a quantity of the rows.

Abstract: A computing system provides a reference image and a current image representing a territory at different times. The computing system determines a partition of the reference image into a first relevant portion and a first non-relevant portion and of the current image into a second relevant portion and a second non-relevant portion according to a partitioning rule. The computing system compares the second relevant portion of the current image with the first relevant portion of the reference image for determining one or more different regions of the current image with respect to the reference image. The computing system determines one or more critical regions of the current image corresponding to the one or more different regions according to a criticality rule. The computing system provides a notification based on the one or more critical regions for use in enforcing land use controls.

Abstract: Methods are provided for determining whether an image captured by a capturing device is clean or dirty. These methods include: receiving the image captured by the image capturing device; splitting the received image into a plurality of image portions according to predefined splitting criteria; performing, for each of at least some of the image portions, a Laplacian filter of the image portion to produce a feature vector including Laplacian filter features of the image portion; providing the feature vectors to a first machine learning module that has been trained to produce a clean/dirty indicator depending on corresponding feature vector, the clean/dirty indicator including a probabilistic value of cleanness or dirtiness of corresponding image portion; and determining whether the image is clean or dirty depending on the clean/dirty indicators produced by the first machine learning module. Systems and computer programs suitable for performing such methods are also provided.

Abstract: In a rectangular region detection mechanism, a to-be-processed image information is received, where the to-be-processed image information comprises at least two images, and where the at least two images comprise a same plurality of first feature points. A plurality of first edge line segments in one of the at least two images are detected. Four first edge line segments from the plurality of first edge line segments are determined. Locations of photographed points corresponding to the plurality of first feature points in a region formed by the four first edge line segments are determined based on location information of the plurality of first feature points. The region is determined as a rectangular region when the photographed points corresponding to the plurality of first feature points in the region are coplanar.

Abstract: An image quality scorer machine accesses a candidate image to be analyzed for visual quality. The image quality scorer machine generates a visual quality score of the candidate image by first generating a prediction of a similarity score for the candidate image. The predicted similarly score of the candidate image may be generated by a process including inputting the candidate image into a neural network that has been trained to detect a set of image features in the candidate image and then to generate a corresponding predicted similarity score based on degrees to which the image features in the set are present in the candidate image. The image quality scorer machine derives the visual quality score based on the predicted similarity score outputted by the neural network. Accordingly, the image quality score machine may provide or store the generated visual quality score of candidate image for subsequent usage.

Abstract: Disclosed is a method for identifying a timepiece including a first component, e.g. the movement, and a second component, e.g. the case. A first zone of the first component of the timepiece is photographed with sufficient enlargement to show therein the tracks and flaws in or on the substrate of the first component in this first zone resulting from the process of manufacturing the timepiece and in particular the tracks or flaws produced when the second component is fitted into the first component. An identification mark (label, chemical or physical modification of the substrate) is applied to a second zone of the second component of the timepiece. These tracks or flaws are converted into a unique code by an appropriate algorithm and this code is associated with at least one item of information contained in the identification mark to form a unique and complete identifier of the item.