A method for generating an object detection dataset and a computer implemented object detection system are disclosed. The method comprises:

receiving a training image dataset comprising a plurality of images that include objects of interest, each image comprising pixel values corresponding to an imaged material generated by a penetrating imager;

generating a thresholded image for each of the plurality of images;

segmenting each thresholded image into images corresponding to objects;

creating a greyscale image per object from the segmented images corresponding to that object by, for each object, calculating an average pixel value for each pixel of the object from corresponding pixels of the object in the segmented images;

forming a greyscale image for the object from the averaged pixels;

storing the greyscale images in a data repository as an object detection dataset.

The present specification relates to a method for enabling an operator to perform visual layer separation, the method including: retrieving at least one X-ray scan image from a memory in data communication with an inspection system, wherein the image comprises a first area of pixels representative of a target object obscured by a clutter object and a second area of pixels representative of the clutter object; receiving a selection of the pixels representative of the first area; receiving a selection of the pixels representative of the second area; determining if the selected second area meets a predefined quality threshold; if the selected second area meets the predefined quality threshold, generating a modified at least one X-ray image; and if the selected second area does not meet the predefined quality threshold, prompting the operator to select a different second area of pixels representative of the clutter object.

Among other things, one or more systems and/or techniques for visually augmenting regions within images are provided herein. An image of an object, such as a bag, is segmented to identify an item (e.g., a metal gun barrel). Features of the item are extracted from voxels representing the item within the image (e.g., voxels within a first region), such as a size, shape, density, and orientation of the item. Response to the features of the item matching predefined features of a target item to detect, one or more additional regions are identified, such as a second region proximate to the first region based upon a location of the second region corresponding to where a connected part of the item (e.g., a plastic handle of the gun) is predicted to be located. The one or more regions are visually distinguished within the image from other regions (e.g., colored, highlighted, etc.).

An information processing device includes an association information acquiring unit, a first position information acquiring unit, and an output control unit. The association information acquiring unit acquires association information in which first identification information used for identifying baggage and second identification information used for identifying an owner of baggage identified by the first identification information are associated with each other. The first position information acquiring unit acquires position information of target baggage that is baggage identified by the first identification information included in the association information. The output control unit causes a mobile terminal held by a target owner who is an owner of the baggage identified by the second identification information associated with the first identification information relating to the target baggage in the association information to output information based on the position information of the target baggage.

A method for inspecting cargo with is disclosed. The method includes scanning the cargo with a matrix including at least two rows of detectors, wherein each zone of the cargo irradiated by a first X ray pulse is irradiated by at least one second X ray pulse, and a radiation corresponding to the first X ray pulse is detected by a first row of the matrix, and a radiation corresponding to the at least one second pulse is detected by at least one second row of the matrix, generating a first image of the cargo and at least one second image of the cargo, determining, for each zone of the cargo irradiated, a local mutual parasitic displacement between the cargo and the matrix, determining a total mutual parasitic displacement, and generating a corrected image of the cargo without the mutual parasitic displacement.

Apparatus and associated methods relate to a method of non-contact motion detection. A one-dimensional optical sensor detects motion of a target or objects on a conveyor belt through a continuous measurement of targets or objects and a real-time comparison of the pixel images captured by the one-dimensional optical sensor. In an illustrative embodiment, a one-dimensional sensor may be configured to determine motion of objects based on changes to the captured intensities of pixel images over time. The sensor may continually capture photoelectric pixel images and compare a current pixel image with a previous pixel image to determine a frame differential image value. The frame differential image value is evaluated against a predetermined threshold over a predetermined time period. Based on the evaluation, a signal is output indicating whether the objects on the conveyor belt are moving or jammed.

First scanned images of the first container are received from a scanning device that show the contents of the interior of the first container before the first container is cut and opened. Second scanned images that are of the contents of the first container after the first container is cut and opened are also received. The images are analyzed and, based upon the analysis, selective modifications to the operating parameters of the container opening machine are determined and made.

A computing-device implemented system and method for identifying an item in an x-ray image is described. The method includes training a machine learning algorithm with at least one training data set of x-ray images to generate at least one machine-learned model. The method further includes receiving at least one rendered x-ray image that includes an item, identifying the item using the at least one model, and generating an automated detection indication associated with the item.

A method, apparatus, system, and computer program product for monitoring a platform. Images are received by a computer system from a sensor system positioned to monitor movement of human beings relative to the platform. A set of the human beings is identified by the computer system in the images. The movement of the set of the human beings relative to the platform is determined by the computer system using the images. A count of the human beings on the platform is determined by the computer system based on the movement determined for the set of the human beings. A set of actions is performed by the computer system based on the count of the human beings on the platform.

A system is provided which utilizes multiple combinations of object location technology to locate objects and direct users to them, and which provides reliable owner recognition and ownership verification with the use of displayed augmented reality with a predefined image of the object and/or the user. Further, the system utilizes augmented reality fingerprint markers. When the augmented reality fingerprint marker is positioned on an object and scanned with a smart device, information relating to the object is superimposed on the object displayed on the smart device.