A method identifies an article by associating an image of the article with stored article data. The method includes: A) creating the image of the article; B) extracting image features from the image; and C) extracting article features from the stored article data. The method step C) are configured to be carried out before, during, or after method steps A) and B). The following method steps are then carried out: D) comparing the image features to the article features; E) output of association information of the image with the stored article data.

An image processing apparatus (100) includes a determination unit configured to determine, on the basis of color information of a detected writing target, color information of an output image generated from a writing content image that is an image of a writing content written on the writing target.

Introduced here is a system for optically tracking displacement with high precision across one or more axes. To track displacement of an object, images that are generated by a plurality of optical sensors can be compared against one another. For example, images that are generated by a first optical sensor can be compared against images that are generated by a second optical sensor. Because the first and second optical sensors are in a fixed spatial relationship with one another, displacement of the object can be established based on the degree to which a given image generated by the first optical sensor matches another image generated by the second optical sensor.

Methods and systems are disclosed for image process biological samples to infer biomarker values. An image of a biological sample can be accessed. The image can be segmented into a set of patches. Edge detection performed on each patch can be used to identify one or more biological features represented by the patch. An indication of the one or more features of each patch may be used to generate one or more image level metrics. A value of a biomarker may be inferred using the one or more image level metrics. The value of the biomarker can then be output.

Described is a system for counting stacked items using image analysis. In one implementation, an image of an inventory location with stacked items is obtained and processed to determine the number of items stacked at the inventory location. In some instances, the item closest to the camera that obtains the image may be the only item viewable in the image. Using image analysis, such as depth mapping or Histogram of Oriented Gradients (HOG) algorithms, the distance of the item from the camera and the shelf of the inventory location can be determined. Using this information, and known dimension information for the item, a count of the number of items stacked at an inventory location may be determined.

[Problem] To shorten the processing time without performing complicated processing during image reading. [Solution] The present disclosure provides an image processing apparatus that includes: a dividing unit that divides a detection region for detecting a feature value of an image into a plurality of regions; a decimation processing unit that performs a decimation process on a pixel value for each of the regions; and a histogram calculating unit that interpolates a pixel value having undergone the decimation process to calculate a histogram of pixel values of the regions. With this configuration, it is possible to shorten the processing time without performing complicated processing during image reading.

A method in a navigational controller includes: controlling a ceiling-facing camera of a mobile automation apparatus to capture a stream of images of a facility ceiling; activating a primary localization mode including: (i) detecting primary features in the captured image stream; and (ii) updating, based on the primary features, an estimated pose of the mobile automation apparatus and a confidence level corresponding to the estimated pose; determining whether the confidence level exceeds a confidence threshold; when the confidence level does not exceed the threshold, switching to a secondary localization mode including: (i) detecting secondary features in the captured image stream; (ii) updating the estimated pose and the confidence level based on the secondary features; and (iii) searching the image stream for the primary features; and responsive to detecting the primary features in the image stream, re-activating the primary localization mode.

An image processing method is disclosed. The image processing method includes setting n reference pixels around a pixel of interest, where n is an integer, sequentially comparing a pixel value of the pixel of interest with a pixel value of each reference pixel, counting a number of the reference pixels whose pixel values are less than or equal to the pixel value of the pixel of interest, incrementing a histogram value of each reference pixel by 1 to compare with a preset inclination limit value, counting a number of the reference pixels satisfying both a condition that the reference pixel value is less than or equal to the pixel value of the pixel of interest and a condition that the histogram value is less than or equal to the inclination limit value so as to obtain a true-in-both count value, and proportionally distributing the true-in-both count value for output.

A waveguide apparatus includes a planar waveguide and at least one optical diffraction element (DOE) that provides a plurality of optical paths between an exterior and interior of the planar waveguide. A phase profile of the DOE may combine a linear diffraction grating with a circular lens, to shape a wave front and produce beams with desired focus. Waveguide apparati may be assembled to create multiple focal planes. The DOE may have a low diffraction efficiency, and planar waveguides may be transparent when viewed normally, allowing passage of light from an ambient environment (e.g., real world) useful in AR systems. Light may be returned for temporally sequentially passes through the planar waveguide. The DOE(s) may be fixed or may have dynamically adjustable characteristics. An optical coupler system may couple images to the waveguide apparatus from a projector, for instance a biaxially scanning cantilevered optical fiber tip.

A system for detecting an anomaly in a video of a factory automation scene is disclosed. The system may accept the video; accept a set of training feature vectors derived from spatio-temporal regions of a training video, where a spatio-temporal region is associated with one or multiple training feature vectors; partition the video into multiple sequences of video volumes; produce a sequence of binary difference images for each of the video volumes; count occurrences of each of predetermined patterns of pixels in each binary difference image for each of the video volumes to produce an input feature vector including an input motion feature vector defining a temporal variation of counts of the predetermined patterns for each of the video volumes; produce a set of distances based on the produced input feature vectors and the set of training feature vectors; and detect the anomaly based on the produced set of distances.