Abstract: A computer-implemented method, for verifying an electronic device user, comprising the steps of issuing at least one action instruction to an electronic device user using a notification mechanism of the electronic device; recording response data from a plurality of data acquisition systems of the electronic device, the response data pertaining to the user's response to the at least one action instruction; processing the response data to form classification scores; combining the classification scores to form a classification value; and verifying the user if the classification value satisfies a threshold, wherein each of the at least one action instruction comprises a liveness challenge.

Abstract: There is disclosed a method of training an RPA robot to use a GUI. The method comprises capturing video of the GUI as an operator uses the GUI to carry out a process; capturing a sequence of events triggered as the operator uses the GUI to carry out said process; and analyzing said video and said sequence of events to thereby generate a workflow. The workflow, when executed by an RPA robot, causes the RPA robot to carry out said process using the GUI.

Abstract: A computer-implemented method for aligning a set of images which have shared structural characteristics, such as images of an official document. The method comprises acquiring image data comprising a set of images and applying, using a first deep neural network, at least one image transform to the image data to form aligned image data in which each image of the set of images is substantially aligned with a template image. Then, the aligned image data is compressed and the image data reconstructed from the compressed image data, and a set of aligned images is output from the reconstructed image data. The set of aligned images may be annotated for automated official document authentication.

Abstract: A computer-implemented method for assessing if a character in a sample image is formed from a predefined selection of characters, comprising: processing a sample image with an alignment network to form a corrective transformation; applying the corrective transformation to the sample image to form a transformed image; computing a similarity of the transformed image with a corresponding reference image of a character from a predefined selection of characters to form a similarity score; and declaring the sample image not to comprise the character from the predefined selection of characters if the similarity score is less than a threshold.

Abstract: A computer-implemented method for assessing if characters in a sample image are formed from a predefined font. The method comprises forming a first embedded space representation for the predefined font, extracting sample characters from the sample image, forming a second embedded space presentation of the sample characters, and comparing the first and second embedded space representation to assess if the sample characters are of the predefined font.

Abstract: The present invention relates to a method of preventing sensitive data received via a remote access protocol from being output to a human operator. The method comprises receiving, from a remote server via a remote access protocol, a user interface of an application executing on the remote server; receiving, from the remote server, a text-based representation of the application; identifying sensitive data in the user interface and/or the text-based representation of the application using one or more preselected filters; modifying the user interface to remove the identified sensitive data; outputting the modified user interface to one or more output peripherals of a computer for receipt by the human operator.

Abstract: A computer-implemented method for classifying a document type of a document in an image and extracting data from the classified document comprising acquiring image data that comprises data relating to at least a part of the document. Textual classification of the document image is then attempted by machine recognition of textual characters to obtain classification data; and using the classification data to classify the document in the image.

Abstract: A computer-implemented method for determining whether images of faces contained in a document correspond to each other. The method comprises acquiring image data pertaining to the document and performing facial detection on the image data to detect one or more facial representations existing within the document. If two or more facial representations are detected, a first facial representation and a second facial representation are selected, and determination of whether the image of a face of the first facial representation corresponds to the image of a face of the second facial representation is performed.

Abstract: A computer-implemented method, for verifying an electronic device user, comprising the steps of issuing at least one action instruction to an electronic device user using a notification mechanism of the electronic device; recording response data from a plurality of data acquisition systems of the electronic device, the response data pertaining to the user's response to the at least one action instruction; processing the response data to form classification scores; combining the classification scores to form a classification value; and verifying the user if the classification value satisfies a threshold, wherein each of the at least one action instruction comprises a liveness challenge.

Abstract: A computer-implemented method for aligning a set of images which have shared structural characteristics, such as images of an official document. The method comprises acquiring image data comprising a set of images and applying, using a first deep neural network, at least one image transform to the image data to form aligned image data in which each image of the set of images is substantially aligned with a template image. Then, the aligned image data is compressed and the image data reconstructed from the compressed image data, and a set of aligned images is output from the reconstructed image data. The set of aligned images may be annotated for automated official document authentication.

Abstract: A computer-implemented method for assessing if a character in a sample image is formed from a predefined selection of characters, comprising: processing a sample image with an alignment network to form a corrective transformation; applying the corrective transformation to the sample image to form a transformed image; computing a similarity of the transformed image with a corresponding reference image of a character from a predefined selection of characters to form a similarity score; and declaring the sample image not to comprise the character from the predefined selection of characters if the similarity score is less than a threshold.

Abstract: A computer-implemented method for determining whether images of faces contained in a document correspond to each other. The method comprises acquiring image data pertaining to the document and performing facial detection on the image data to detect one or more facial representations existing within the document. If two or more facial representations are detected, a first facial representation and a second facial representation are selected, and determination of whether the image of a face of the first facial representation corresponds to the image of a face of the second facial representation is performed.

Abstract: A computer-implemented method for classifying a document type of a document in an image and extracting data from the classified document comprising acquiring image data that comprises data relating to at least a part of the document. Textual classification of the document image is then attempted by machine recognition of textual characters to obtain classification data; and using the classification data to classify the document in the image.

Abstract: A computer-implemented method for assessing if characters in a sample image are formed from a predefined font. The method comprises forming a first embedded space representation for the predefined font, extracting sample characters from the sample image, forming a second embedded space presentation of the sample characters, and comparing the first and second embedded space representation to assess if the sample characters are of the predefined font.