An HD map system represents landmarks on a high definition map for autonomous vehicle navigation, including describing spatial location of lanes of a road and semantic information about each lane, and along with traffic signs and landmarks. The system generates lane lines designating lanes of roads based on, for example, mapping of camera image pixels with high probability of being on lane lines into a three-dimensional space, and locating/connecting center lines of the lane lines. The system builds a large connected network of lane elements and their connections as a lane element graph. The system also represents traffic signs based on camera images and detection and ranging sensor depth maps. These landmarks are used in building a high definition map that allows autonomous vehicles to safely navigate through their environments.

In some implementations, a device may detect edges in an image, and may identify, based on the edges, a rectangle that bounds a document in the image. The device may detect lines in the image, and may identify edge candidate lines by discarding one or more of the lines. The device may identify intersection points where lines, included in the edge candidate lines, intersect with one another. The device may identify corner candidate points by discarding one or more points included in the intersection points, and may identify a corner point included in the corner candidate points. The corner point may be a point, included in the corner candidate points, that is closest to one corner of the bounding rectangle. The device may perform perspective correction on the image of the document based on identifying the corner point.

A processing method for high-order tensor data, which can avoid that the vectorization process of the image observation sample set damage the internal structure of the data, simplify the large amount of redundant information in the high-order tensor data in the image observation sample set, and improve the image processing speed. In this processing method for high-order tensor data, the high-order tensor data are divided into three parts: the shared subspace component, the personality subspace component and the noise part; the shared subspace component and the personality subspace component respectively represent the high-order tensor data as a group of linear combination of the tensor base and the vector coefficient; the variational EM method is used to solve the base tensor and the vector coefficient; design a classifier to classify the test samples by comparing the edge distribution of samples.

Provided are an image processing apparatus, a control method, and a control program to more accurately remove the shading from the image including the shading. An image processing apparatus includes a storage device to store a shading pattern in which a condition of gradation values of a target pixel and a plurality of pixels having a predetermined positional relationship with respect to the target pixel are set, an acquisition module to acquire a multiple value image, a binary image generation module to generate a binary image from the multiple value image, a detection module to detect a pixel satisfying the condition set in the shading pattern from the multiple value image as a part of a shading, a shading removal pattern generation module to generate a shading removal pattern for removing the detected shading, based on the multiple value image, a shading removal image generation module to generate a shading removal image by applying the shading removal pattern to the binary image, and an output device to output the shading removal image or information generated using the shading removal image.

According to one embodiment, a reading system includes a processing device. The processing device includes an extractor, a line thinner, a setter, and an identifier. The extractor extracts a partial image from an input image. A character of a segment display is imaged in the partial image. The segment display includes a plurality of segments. The line thinner thins a cluster of pixels representing a character in the partial image. The setter sets, in the partial image, a plurality of determination regions corresponding respectively to the plurality of segments. The identifier detects a number of pixels included in the thinned cluster for each of the plurality of determination regions, and identifies the character based on a detection result.

Methods, systems, and computer program products for generating search determinations for assortment planning and buying using visual sketches are provided herein. A computer-implemented method includes processing a query image by identifying one or more visual features in the query image and applying at least one nearest neighbor algorithm to the one or more identified visual features; identifying, from one or more databases, multiple images based at least in part on the processing; generating a result set by applying one or more smoothing algorithms to the multiple identified images; generating at least one sketch based at least in part on the result set; and outputting the at least one generated sketch to one or more users via a user interface.

One aspect of the present invention is to provide systems and methods that improve the accuracy of an assay that comprise at least one or more parameters each having a random error.

Image annotation includes: accessing an image and a plurality of annotation data sets for the image, wherein the plurality of annotation data sets are made by a plurality of contributors, and the image has a plurality of original image channels; aggregating the plurality of annotation data sets to obtain an aggregated annotation data set for the image; and outputting the aggregated annotation data set. Aggregating the plurality of annotation data sets to obtain an aggregated annotation data set for the image includes: generating an additional image channel based at least in part on weight averages of confidence measures of the plurality of contributors; and applying an object detection model to at least a part of the plurality of original image channels and at least a part of the additional image channel to generate the aggregated annotation data set.

The disclosure relates to a method for imaging by a medical X-ray device. In order to enable a reduction of an X-ray dose during imaging, the method includes: determining a viewing parameter of a viewer with reference to a future display of an image recorded by the X-ray device, determining a recording parameter set including an X-ray dose at least partially in dependence on the viewing parameter, and recording an image by the X-ray device using the recording parameter set.

A method for generating training data for object detection is provided. The method includes dividing an image into a plurality of sliced images. The image includes meta information for an object in the image, the meta information including bounding box information associated with a bounding box surrounding the object, and marker information for markers associated with the object, the markers being located within the bounding box. The method includes designating at least one sliced object image from among the plurality of sliced images, at least a portion of the bounding box overlapping with each of the respective sliced object images. The method also includes designating at least one training data image from among the designated sliced object images based on the marker information. The method also includes generating the training data from the designated training data images.