Abstract: Methods and systems for image scoring and analysis are provided. Scored and analyzed images may include digital pathology images. Image scoring and analysis methods may include techniques to identify nuclei and determine membrane staining extent through the use of a priori models. Image scoring and analysis methods may include techniques for membrane intensity determination. Images may be scored based on an extent of membrane staining and membrane intensity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying objects in images. One of the methods includes obtaining a first training image; down-sampling the first training image to generate a low-resolution first training image; processing the low-resolution first training image using a first neural network to generate a plurality of features of the low-resolution first training image and first scores for the low-resolution first training image; processing the first scores and the features of the low-resolution first training image using an initial patch locator neural network to generate an initial location of an initial patch of the first training image; locally perturbing the initial location to select an adjusted location for the initial patch of the first training image; and updating the current values of the parameters of the initial patch locator neural network to generate updated values using the adjusted location.

Abstract: A system for automated car counting comprises a satellite-based image collection subsystem; a data storage subsystem; and an analysis software module stored and operating on a computer coupled to the data storage subsystem. The satellite-based image collection subsystem collects images corresponding to a plurality of areas of interest and stores them in the data storage subsystem. The analysis module: (a) retrieves images corresponding to an area of interest from the data storage subsystem; (b) identifies a parking space in an image; (c) determines if there is a car located in the parking space; (d) determines a location, size, and angular direction of a car in a parking space; (e) determines an amount of overlap of a car with an adjacent parking space; (f) iterates steps (b)-(e) until no unprocessed parking spaces remain; and (g) iterates steps (a)-(f) until no unprocessed images corresponding to areas of interest remain.

Abstract: Disclosed herein are techniques for enhancing the accuracy of atlas-based auto-segmentation (ABAS) using an automated structure classifier that was trained using a machine learning algorithm. Also disclosed is a technique for training the automated structure classifier using atlas data applied to the machine learning algorithm.

Abstract: Disclosed herein are techniques for performing automated structure delineation on image data using trained landmark detectors and a shape refinement tool. The landmark detectors can be trained to detect a landmark in the image data based on image features that are indicative of intensity variations over a plurality of windows of the image data points. A machine-learning algorithm can be used to train the landmark detectors. The landmarks in the image data that are detected by the trained landmark detects can be used to initialize an iterative shape refinement to thereby compute a refined shape estimate for a structure of interest such as a prostate.

Abstract: Provided are an image processing apparatus, image processing method and a computer-readable, non-transitory medium that can accurately detect document edges from a readout image. The image processing apparatus includes a first edge pixel detector for detecting a plurality of first edge pixels from an input image, a straight line detector for detecting a straight line from the first edge pixels, a classifying module for classifying the first edge pixels into on-line edge pixels and non-on-line edge pixels, a second edge pixel detector for detecting second edge pixels located between two of the on-line edge pixels, when there is any one of the non-on-line edge pixels between two of the on-line edge pixels, and a determining module for determining whether the non-on-line edge pixel represents a document edge, based on whether the two on-line edge pixels are connected by the second edge pixels via the non-on-line edge pixel.

Abstract: A computer implemented method and apparatus for managing deadline content in a document. The method comprises extracting deadline content from a document; comparing the extracted deadline content to content in one or more existing deadline profiles; and providing for storage on a cloud server, at least one of the extracted deadline content when the extracted deadline content matches the content in an existing deadline profile, or the extracted deadline content and a new deadline profile for the document when the extracted deadline content does not match an existing deadline profile.

Abstract: Audiovisual content presentation to users has evolved from users receiving hardcopy printed materials to their searching and retrieving information by accessing any of hundreds of millions of web sites and billions of web pages. User retrieval being performed on a wide variety of platforms from high performance PCs to low performance cellular telephones. Accordingly substantial limitations exist in initially displaying this audiovisual content as well as when users dynamically manipulate browser dimensions or move through the content. Further additional limitations exist for those authoring both online and traditional content to manipulate sourced content to provide the published content. As such a requirement exists for dynamically resizing images that respects the information content within the audiovisual content.

Abstract: The present invention discloses a method and apparatus for page proofreading, the method comprising: splitting a document before modification to at least one single page document file before modification and splitting a document after modification to at least one single page document file after modification; adding the at least one single page document before modification into a first page, adding the at least one single page document after modification into a second page; setting correlativity between each of the single page documents before modification in the first page and each of the single page documents after modification in the second page; comparing pixel elements of the previews of the single page document before modification and the single page document after modification for all of the first pages and the second pages that correlated with each other; if there are different parts, displaying the comparison result by marking the different parts.

Abstract: An object of the present invention is to provide a positioning system which makes it possible to perform positioning processing in a positioning target mobile object with a smaller calculation amount. A scenery image database according to an aspect of the present invention is characterized by comprising a plurality of scenery image data and image acquisition locations at which the scenery image data have been acquired are correlated with each other and stored, wherein each of the plurality of scenery image data include a feature amount of a feature point corresponding to a thing other than a thing of which a location or a shape is unlikely to be kept as it is on the real world during a period larger than or equal to a predetermined period.

Abstract: A technique is provided for measuring an object based on multiple views. The technique includes registering each of the plurality of images and a first model of the object with one another and reconstructing a second model of the object based on the plurality of images and the first model registered with one another.

Abstract: The present invention is directed to an apparatus which can acquire, readout and perceive a scene based on the insertion, or embedding of photosensitive elements into or on a transparent or semi-transparent substrate such as glass or plastic. The substrate itself may act as the optical device which deflects the photons of an incident image into the photosensitive elements. A digital neural memory can be trained to recognize patterns in the incident photons. The photosensitive elements and digital neural memory elements may be arranged with light elements controlled in accordance with the patterns detected. In one application, intelligent lighting units provide light while monitoring surroundings and/or adjusting light according to such surroundings. In another application, intelligent displays display images and/or video while monitoring surroundings and/or adjusting the displayed images and/or video in accordance with such surroundings.

Abstract: An image processing method and apparatus is provided. The image processing method includes steps of: generating a first scale binary image from an image, wherein the first scale is smaller than the original scale of the image; detecting at least one text line in the image based on the first scale binary image; generating a second scale binary image from the image, wherein the second scale is larger than the first scale; for each text line, calculating a similarity between corresponding sections in the first scale binary image and the second scale binary image, and removing the text line for which the similarity is lower than a predetermined level; for one or more of the remaining text line(s), performing OCR on corresponding section(s) in the second scale binary image to determine character orientation(s) of corresponding text line(s); and determining the orientation of the image according to the determined character orientation(s).

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, system can measure the basion-dens interval (BDI), which has been shown to be an effective indicator of ligament injury within the occipito-cervical complex (“OCC”) that may not present with other symptoms, is not revealed with standard CT imaging, and is of mortal danger to the patient if untreated. The system can automate interpreting CT scanned images and alert medical personnel about the risk of OCC ligament damage.

Abstract: An image file for storing a still digital image and metadata related to the still digital image, the image file including digital image data representing the still digital image, and metadata that categorizes the still digital image as an important digital image, wherein the categorization uses a range of levels and the range of levels includes at least three different integer values.

Abstract: A defect detection system for computerized detection of defects in an inspected object based on processing of an inspection image generated by collecting signals arriving from the inspected object, the system including: an interface for obtaining an inspected noise-indicative value and multiple reference noise-indicative values, the inspected noise-indicative value representative of an analyzed pixel and each of the reference noise-indicative values representative of a reference pixel among a plurality of reference pixels; and a processor, including: a noise analysis module, configured to compute a representative noise-indicative value based on a plurality of noise-indicative values which includes the inspected noise-indicative value and the multiple reference noise-indicative values; and a defect analysis module, configured to calculate a defect-indicative value based on an inspected value representative of the analyzed pixel, and to determine a presence of a defect in the analyzed pixel based on the represe

Abstract: A medical image processing apparatus to accurately identify malignant transformations of probable tumors. The medical image processing apparatus including a specifying mechanism and first, second, and third computing mechanisms. The specifying mechanism specifies a probable tumor from medical image data upon receiving the medical image data obtained by imaging a subject by a single medical imaging apparatus. The first computing mechanism calculates morphological information indicating morphological characteristics of a specified probable disease based on this medical image data. The second computing mechanism calculates functional information of the specified probable disease based on this medical image data. The third computing mechanism calculates amount of progress characteristics indicating the extent of the probable disease based on the morphological information and functional information.

Abstract: A defect detection system for computerized detection of defects, the system including: an interface for receiving inspection image data including information of an analyzed pixel and of a plurality of reference pixels; and a processor, including: a differences analysis module, configured to: (a) calculate differences based on an inspected value representative of the analyzed pixel and on multiple reference values, each of which is representative of a reference pixel among the plurality of reference pixels; wherein the differences analysis module is configured to calculate for each of the reference pixels a difference between the reference value of the reference pixel and the inspected value; and (b) compute a representative difference value based on a plurality of the differences; and a defect analysis module, configured to determine a presence of a defect in the analyzed pixel based on the representative difference value.

Abstract: Various embodiments enable regions of text to be identified in an image captured by a camera of a computing device for preprocessing before being analyzed by a visual recognition engine. For example, each of the identified regions can be analyzed or tested to determine whether a respective region contains a quality associated with poor text recognition results, such as poor contrast, blur, noise, and the like, which can be measured by one or more algorithms. Upon identifying a region with such a quality, an image quality enhancement can be automatically applied to the respective region without user instruction or intervention. Accordingly, once each region has been cleared of the quality associated with poor recognition, the regions of text can be processed with a visual recognition algorithm or engine.

Abstract: Disclosed is a computing device that can perform automatic image rectification for a visual search. A method implemented at a computing device includes receiving one or more images from an image capture device, storing the one or more images with the computing device, building a three dimensional (3D) geometric model for one or more potential objects of interest within an environment based on at least one image of the one or more images, and automatically creating at least one rectified image having at least one potential object of interest for a visual search.