A system for detecting containers that have been tampered with includes one or more tamper detecting tape nodes attached to a container storing one or more assets, and a tracking system controller configured to receive data from the one or more scanning tape nodes, track the container and the one or more assets, and maintain a database comprising data on the container and the one or more assets, according to some embodiments. Each of the one or more tamper detecting tape nodes comprising a first type of wireless communication system and configured to detect tampering events that occur to the container, store tampering event data corresponding to the tampering events in a storage or memory of the tamper detecting tape node, and wireless communicate with other wireless nodes of the system.

A hologram detection method according to an aspect of the disclosure, includes: inputting a first image, obtained by capturing a detection object on the basis of first flash intensity, to a neural network model to obtain a first detection result value representing the detection or not of a hologram for each of predetermined at least one detection unit regions; and comparing a threshold value with the first detection result value obtained for each detection unit region to determine the detection or not of a hologram in the first image and a first detection unit region where a hologram is detected.

A document authenticity identification method is provided. A dynamic anti-counterfeiting point is detected in each document image of a subset of a plurality of document images. A static anti-counterfeiting point is detected in a document image of the plurality of document images. A static anti-counterfeiting point feature is generated based on image feature information of the static anti-counterfeiting point that is extracted from the document image. A dynamic anti-counterfeiting point feature is generated based on image feature information of the dynamic anti-counterfeiting point and variation feature information of the dynamic anti-counterfeiting point. A first authenticity result corresponding to the static anti-counterfeiting point is determined based on the static anti-counterfeiting point feature. A second authenticity result corresponding to the dynamic anti-counterfeiting point is determined based on the dynamic anti-counterfeiting point feature. Authenticity of the document is determined based on the first authenticity result and the second authenticity result.

This specification includes a method that includes receiving, at one or more processing devices at one or more locations, one or more image frames; receiving a set of signals representing outputs of one or more sensors of a device; estimating, based on the one or more image frames, a first set of one or more motion values; estimating, based on the set of signals, a second set of one or more motion values; determining that a degree of correlation between (i) a first motion represented by the first set of one or more motion values and (ii) a second motion represented by the second set of one or more motion values fails to satisfy a threshold condition; and in response to determining that the degree of correlation fails to satisfy the threshold condition, determining presence of an adverse condition associated with the device.

The present invention is to provide a computer system, and a method and a program for managing an advertising medium that easily identify an advertising medium. The computer system for managing an advertising medium outputs an identification image embedding the identification information of the advertising medium to the advertising medium, analyzes the shot image of the advertising medium outputting the identification image and reads the identification information of the advertising medium, and registers the identification information in a database.

An information processing system includes an array sensor with a pixel array having a plurality of one-dimensionally or two-dimensionally arranged pixels including a light-receiving element that receives visible or non-visible light, a hash value generator that generates a hash value from captured-image data based on a photoelectric conversion performed by the pixel array, and an encryption processing section that performs processing of encrypting the hash value; an acquisition section that acquires the captured-image data and the encrypted hash value; a decryption processing section that decrypts the acquired encrypted hash value; a hash value calculator that calculates a hash value from the acquired captured-image data; a hash value comparing section that compares the hash value obtained by the decryption with the calculated hash value; and a falsification determination section that determines whether the acquired captured-image data has been falsified, based on a comparison result of the hash values.

Described are methods and systems for detecting fraud in documents. First images of a first set of genuine documents and second images of a second set of genuine documents are obtained. A printed feature, spacings between printed features in the first images, and positions of printed features in the second images are selected. Selected features, spacings and positions are annotated to obtain original landmark locations for each printed feature, spacing and position. Annotated features, spacings and positions are transformed to obtain transformed features, transformed spacings and transformed positions. The transformed features, spacings and positions are combined with a noise model to generate modified features, modified spacings and modified positions. Each modified feature, modified spacing and modified position comprises annotations indicating modified landmark locations. Input data for a machine learning model is generated using original landmark locations and modified landmark locations. The machine learning model is trained using the input data.

The system for in-vehicle video conferencing (200) includes:

an acquisition module (201) for acquiring data of facial characteristic points of a user (A) in the vehicle (100) during a video conference call in which said user (A) participates;
a video synthesizer (202A) for producing an artificial video of the face of the user in the vehicle (100) from the acquired data of facial characteristic points,
a communication device (203) for transmitting the artificial video of the face of the user through a communication network (300) in the video conference call.

The invention relates to a method and system for optical product authentication, in which a product is labeled with optically active particles, a reference image is recorded in a registration step and a recognition image of the optically active particles is recorded in a recognition step. The product is then authenticated by comparing image data or a coding derived from image data in the registration step versus the recognition step.

A machine learning system may automatically produce classifier algorithms and configuration parameters by selecting them into a set of predetermined unitary algorithms and associated parametrization values. Multiple digital representations of input object items may be produced by varying the position and orientation of the object to be classified and/or of the sensor to capture a digital representation of the object, and/or by varying a physical environment parameter which changes the digital representation capture of the object by the sensor. A robot arm or a conveyor may vary the object and/or the sensor positions and orientations. The machine learning system may employ genetic programming to facilitate the production of classifiers suitable for the classification of multiple digital representations of input object items. The machine learning system may automatically generate reference template signals as configuration parameters for the unitary algorithms to facilitate the production of classifiers suitable for the classification of multiple digital representations of input object items.