Abstract: One example embodiment is a method to embed a watermark image into a host image such that a watermarked image is generated. The method divides a host image into an Red (R) component, a Green (G) component, and a Blue (B) component, and partitions each component of the R, G, and B components into non-overlapping blocks from which embedding blocks are selected to embed watermark information such that a watermarked image is generated.

Abstract: The present disclosure relates generally to signal processing, including processing digital watermarking. One claim recites a detector apparatus comprising: memory for storing data representing color image data comprising red color data and green color data, in which the red color data comprises digital watermarking including a first polarity and the green color data comprises the digital watermarking including a second polarity that is inversely related to the first polarity; means for selectively weighting the red color data and the green color data so that the digital watermarking is emphasized while image content is de-emphasized when weighted red color data and weighted green color data are combined; means for detecting the digital watermarking from combined, weighted red color data and weighted green color data; and more or more processors configured for outputting data corresponding to detected digital watermarking. Of course, different combinations and claims are provided too.

Abstract: A method and apparatus for generating 3D-maps for acquiring three-dimensional (3D) maps are presented. The method includes analyzing at least one image acquired by a passive sensor to identify a plurality of objects in the at least one image; classifying the plurality of objects; determining, based on the classification, whether to passively measure a distance to each of the plurality of objects; passively measuring the distance to at least one of the plurality of objects based on the determination; actively measuring a distance to some of the plurality of objects, wherein the distance to one of the same of the plurality of objects is actively measured when the distance to the object cannot be passively measured; and generating a 3D map of a scene based on the distance measured to each of the plurality of objects.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for recognizing object sub-types in images. One of the methods includes receiving training data; selecting training data for an image; determining whether to randomly permute a value of a property of the selected image; providing, to a deep neural network, the particular training data or the randomly permuted particular training data; receiving, from the deep neural network, output data indicating a predicted label for an object sub-type for an object depicted in the selected image, and a confidence score that represents a likelihood that the object has the object sub-type; updating one or more weights in the deep neural network using an expected output value, the predicted label, and the confidence score; and providing the deep neural network to a mobile device for use detecting whether one or more images depict objects having the particular object sub-type.

Abstract: An information processing apparatus includes: a gaze position detection section that detects a gaze position of a user with respect to a display screen; a position information acquisition section that acquires position information of the user; and a control section that judges, based on the detected gaze position, a scene and an object in the scene that the user focuses in a content displayed on the display screen, and generates search information from the judged object and the acquired position information.

Abstract: A method is for processing a first image data set including a first image value tuple associated with a volume element of a region of an object to be imaged. In an embodiment, a second image data set is generated based upon the first image data set, including a second image value tuple associated with the volume element, a base material decomposition being capable of being carried based upon the second image data set and based upon a base material set; a starting area and a target area are selected as a function of the base material set, the first image value tuple being located in the starting area; the second image value tuple is ascertained based upon the first image value tuple, the second image value tuple being associated with the first image value tuple via image value tuple imaging and being located in the target area.

Abstract: A system and method are provided for medical imaging that includes acquiring, during a common imaging acquisition process, rotational, x-ray volume image data and x-ray tomosynthesis image data from a subject. The method includes reconstructing a time-resolved three-dimensional (3D) image volume from the rotational, x-ray volume image data and producing a four-dimensional (4D) image series of the subject with resolved overlapping features by selectively combining the time-resolved 3D image volume and the x-ray tomosynthesis imaging data.

Abstract: A method of segmenting a target organ of the body in medical images, the method comprising: providing a probabilistic atlas with probabilities for a presence of the target organ at different locations relative to a bounding region of the target organ; providing one or more medical test images; for each test image, identifying, at least provisionally, a location of a bounding region for the target organ in the test image; and for each test image, using the probabilities from the probabilistic atlas to segment the target organ in the test image, with the segmenting performed by a data processor.

Abstract: The present disclosures relates generally to image signal processing and encoding signal within imagery. One claim recites a method comprising: obtaining data representing captured imagery, the captured imagery depicting packaging including digital watermarking, the digital watermarking including an orientation signal that is detectable in a transform domain; generating a n-dimensional feature set of the data representing captured imagery, the n-dimensional feature set representing the captured imagery in a spatial domain, where n is an integer great than 13; using a trained classifier to predict the presence of the orientation signal in a transform domain from the feature set in the spatial domain. Of course, other claims and combinations are provided too.

Abstract: Provided are systems, methods, and other embodiments associated with depth-resolved spatial-domain low-coherence quantitative phase microscopy for high-throughput analysis of 3D nanoscale architectural alterations in unstained tissue and cells. A spatial-domain low-coherence quantitative phase microscopy apparatus includes a drOPD mapping module, a transmission phase imaging module, and a bright-field and transmission phase imaging module. The drOPD mapping module includes a reflection-mode low-coherence spectral interferometry for drOPD mapping of unstained tissue. The transmission phase imaging module includes transmission quantitative phase imaging of unstained and stained tissue and produce an image registration reference. The bright-field and transmission phase imaging module includes bright-field imaging of H&E-stained tissue for nuclei identification and pathology correlation.

Abstract: Described herein is a device for traffic light detection. The device comprises a memory and a traffic light detection module. The memory may store information, the information comprising first traffic light data of a first traffic light and second traffic light data of a second traffic light. The traffic light detection module may receive an image comprising a first candidate and a second candidate; determine a first region of interest based, at least in part, on the first traffic light data, the first region of interest comprising the first candidate; determine a second region of interest based, at least in part, on the second traffic light data, the second region of interest comprising the second candidate; and determine a confidence score for a first state of the first candidate, the confidence score based, at least in part, on a spatial relationship factor between the first candidate and the second candidate.

Abstract: The present invention relates to a method for assisting a user in determining a medical condition in a subject from one or more medical images by presenting the user with a list of questions, LOQ, about the subject that are to be answered with an affirmative indication (Y), a negative indication (N) or an unknown indication (X) by input by the user. In response to receiving an answer to one question, the method presents the user with a ranked list of conditions, LOC, and also with an updated LOQ wherein at least the answered question has been removed i.e. the LOQ iteratively collapses or reduces in length. An earlier step of selecting a foundation observation, FO, about the subject reduces the initial LOQ and the possible conditions.

Abstract: A medical image measuring apparatus includes a tissue information label assigning unit that assigns each point of a medical image with a tissue information label representing tissue information each point belongs, a measuring unit that performs measurement in the medical image, and a measurement subject label assigning unit that determines, based on a tissue information label assigned to a measurement point or a point within a region of interest used for the measurement, a measurement subject label representing a measurement subject and assigns the label to a result of the measurement.

Abstract: A computer implemented method for detecting an object in a crowded scene utilizing an image capturing device. The method includes receiving an image of a predetermined area. From the image, the existence of selected portions as representing an entity of a selected class is determined. Each selected portion is assigned an initial confidence value that the selected portion is an entity representative of a selected class. Each selected portion is evaluated with each other to determine a context confidence value. The context confidence value and initial confidence value are utilized to determine which of the one or more selected portions are entities of a selected class.

Abstract: This specification describes technologies relating to biometric authentication based on images of the eye. In general, one aspect of the subject matter described in this specification can be embodied in methods that include obtaining images of a subject including a view of an eye. The methods may further include determining a behavioral metric based on detected movement of the eye as the eye appears in a plurality of the images, determining a spatial metric based on a distance from a sensor to a landmark that appears in a plurality of the images each having a different respective focus distance, and determining a reflectance metric based on detected changes in surface glare or specular reflection patterns on a surface of the eye. The methods may further include determining a score based on the behavioral, spatial, and reflectance metrics and rejecting or accepting the one or more images based on the score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing cell images using neural networks. One of the methods includes obtaining data comprising an input image of one or more biological cells illuminated with an optical microscopy technique; processing the data using a stained cell neural network; and processing the one or more stained cell images using a cell characteristic neural network, wherein the cell characteristic neural network has been configured through training to receive the one or more stained cell images and to process the one or more stained cell images to generate a cell characteristic output that characterizes features of the biological cells that are stained in the one or more stained cell images.

Abstract: The invention relates to a method of gaze estimation. As to determine the position of the gaze without calibrating the system used for determining the gaze, the method comprises: detecting at least a location of the center of at least an eye on at least an eye image of a viewer watching at least a video image displayed on a screen; determining at least a first position of the gaze of the viewer on the screen by using the at least a detected location of the center of the at least an eye and a mapping function based on center-bias property of human gaze distribution. The invention also relates to a device configured for estimating the gaze.

Abstract: A computer-implemented method and system are described for locating fingernails of a person's hand in an image. An approximate location of each fingernail in the image is determined. An approximate location of each of a plurality of digit-shape objects in the image is initialized based on the approximate locations of the fingernails, and initially refined based on respective digit-shape object models and corresponding functions. The approximate location of each fingernail sub-shape is further refined based on a respective fingernail model and its corresponding function.

Abstract: A radiography apparatus and a method for controlling the radiography apparatus are provided. The radiography apparatus includes a radiographer configured to acquire a first radiation image of a subject before a contrast reagent is injected into the subject, and acquire a second radiation image of the subject after the contrast reagent is injected into the subject. The radiography apparatus further includes an image processor configured to calculate a difference between data of a pixel of the first radiation image and data of a pixel of the second radiation image, for each of pixels of the first radiation image, and acquire an image of the subject based the difference for each of the pixels of the first radiation image.

Abstract: Embodiments described herein use depth images to extract user behavior, wherein each depth image specifies that a plurality of pixels correspond to a user. In certain embodiments, one or more average extremity positions of a user, which can also be referred to as average positions of extremity blobs, are extracted from a depth image. An application is then updated based on the average positions of extremity blobs.