An image processing system may include an imaging device for capturing an image and an image processing apparatus for processing the image. The imaging device may include an imaging unit for capturing the image, a first recording unit for recording information relating to the image, the information being associated with the image, and a first transmission control unit for controlling transmission of the image to the image processing apparatus. The image processing apparatus may include a reception control unit for controlling reception of the image transmitted from the imaging device, a feature extracting unit for extracting a feature of the received image, a second recording unit for recording the feature, extracted from the image, the feature being associated with the image, and a second transmission control unit for controlling transmission of the feature to the imaging device.

[Problem] To provide a motion condition estimation device, a motion condition estimation method and a motion condition estimation program capable of accurately estimating the motion condition of monitored subjects even in a crowded environment. [Solution] A motion condition estimation device according to the present invention is provided with a quantity estimating means 81 and a motion condition estimating means 82. The quantity estimating means 81 uses a plurality of chronologically consecutive images to estimate a quantity of monitored subjects for each local region in each image. The motion condition estimating means 82 estimates the motion condition of the monitored subjects from chronological changes in the quantities estimated in each local region.

Traffic-counting methods and apparatus are disclosed. The methods may include, in a view of traffic comprising moving objects, identifying first and second regions of interest (ROIs). The methods may also include obtaining first and second image data respectively representing the first and second ROIs. The methods may also include analyzing the first and second image data over time. The methods may further include, based on the analyses of the first and second image data, counting the moving objects and determining moving directions of the moving objects.

This document describes methods, systems and computer program products directed to imaging blood cells. The subject matter described in this document can be embodied in a method of classifying white blood cells (WBCs) in a biological sample on a substrate. The method includes acquiring, by an image acquisition device, a plurality of images of a first location on the substrate, and classifying, by a processor, objects in the plurality of images into WBC classification groups. The method also includes identifying, by a processor, objects from at least some classification groups, as unclassified objects, and displaying, on a user interface, the unclassified objects and at least some of the classified objects.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining whether content rendered on a display is actually visible to a user. In one aspect, a method includes generating and transmitting content presentation data that causes a user device to present, at a display and over a first time period, a content item that includes one or more content portions that are each designated for presentation in a respective first color. For a second time period, the respective first color of a particular content portion is changed to a second color. Visual representation data that includes a visual representation of the display during the second time period is generated and provided. Using the visual representation, an amount of the content item that was visible at the display is determined based on an amount of the particular content portion presented in the second color.

A device for determining normalized occupancy of one or more spaces in a building is disclosed. The device includes a memory and a processor coupled to the memory. The processor is configured to: poll one or more people counting sensors associated with access points to a defined region of the building to obtain counts data from the one or more people counting sensors for a specified time period and historical calibration data for the one or more people counting sensors; and process the counts data and the historical calibration data to determine a normalized occupancy of the defined region during the specified time period.

Various examples of a system for peanut sorting and grading are disclosed herein. The system for grading peanut maturity, can include: a sample feeder configured to supply individual peanuts to an imaging area; a sorting board comprising a plurality of chutes and a plurality of gates, each chute of the plurality of chutes designated for a grade of peanut; and program instructions to obtain the digital image of the individual peanut; determine the grade of the individual peanut; and sort the individual peanut based on the grade of the individual peanut. A method for grading peanut maturity, can include feeding an individual peanut to an imaging area; obtaining a digital image of the individual peanut; determining a grade of the individual peanut based on an average color; and sorting the individual peanut in a chute of a sorting board based on the grade of the individual peanut.

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

Method for detecting spatial coupling comprising the steps of: a. providing a set of data, b. identifying and segmenting a first and a second sets of objects of interest, wherein the objects of the second set are assimilated to punctual objects, c. determining, using a level set function, an expected number of objects of the second set present within a specified range of distances to at least one given object of the first set in case there were no interactions between said at least one given object of the first set and the objects of the second set, d. determining, using a level set function, an actual number of objects of the second set within the same range of distances to the at least one given object of the first set, and e. comparing said expected amount and said determined amount.

A product identification apparatus (20) includes an acquisition unit (210), an image processing unit (220), and a storage processing unit (230). The acquisition unit (210) acquires an image generated by an image capturing apparatus 10. The image includes a product shelf (40) and a product (50). The image processing unit (220) determines a position where continuity of the product shelf (40) is broken by processing the image acquired by the acquisition unit (210), and divides the product shelf (40) into a unit region by using the position. Further, the image processing unit (220) determines a kind and a product name of the product (50) by processing the image acquired by the acquisition unit (210). The storage processing unit (230) causes a storage unit (240) to store product identification information of the product (50) located in the unit region, for each unit region of the product shelf (40).