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公开(公告)号：US11694474B2
公开(公告)日：2023-07-04
申请号：US16667200
申请日：2019-10-29
申请人： ONFIDO LTD
发明人： Pouria Mortazavian , Jacques Cali
CPC分类号： G06F21/32 , G06F17/16 , G06K9/6267 , G06T7/70 , G06V40/45
摘要： 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.
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公开(公告)号：US11258924B2
公开(公告)日：2022-02-22
申请号：US16597626
申请日：2019-10-09
申请人： ONFIDO LTD
摘要： 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.
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公开(公告)号：US20230281821A1
公开(公告)日：2023-09-07
申请号：US17688575
申请日：2022-03-07
申请人： Onfido Ltd.
发明人： Daniele Pizzocchero , Jimmy Moore , Zhiyuan Shi , Christos Sagonas , Mohan Mahadevan , Yuanwei Li
CPC分类号： G06K9/00536 , G06T7/11 , G06T2207/30176 , G06T2207/20084 , G06T2207/20081 , G06T2207/10016 , G06T2207/10004
摘要： Described herein are computerized methods and systems for authentication of a physical document. An image capture device coupled to a mobile device captures images of a physical document, during which the mobile device adjusts operational parameters of the image capture device, resulting in a sequence of images captured using different capture settings. The mobile device partitions the sequence of images into subsets of images, wherein each subset comprises images with a similar alignment of the physical document and captured using the same capture settings. The mobile device processes the subsets of images to identify a region of interest in each image. The mobile device generates a representation of the identified region of interest using the processed images, generates an authentication score for the document using the representation of the identified region of interest, and determines whether the physical document is authentic based upon the authentication score.
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公开(公告)号：US11100322B2
公开(公告)日：2021-08-24
申请号：US16588425
申请日：2019-09-30
申请人： ONFIDO LTD
摘要： 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.
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公开(公告)号：US20190213408A1
公开(公告)日：2019-07-11
申请号：US16245453
申请日：2019-01-11
申请人： ONFIDO LTD
发明人： Jacques Cali , Joao Silva Gomes
CPC分类号： G06K9/00456 , G06F17/214 , G06K9/00463 , G06K9/3233 , G06K9/6828 , G06K2209/01 , G06N3/0454
摘要： 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.
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公开(公告)号：US12067796B2
公开(公告)日：2024-08-20
申请号：US17719199
申请日：2022-04-12
申请人： Onfido Ltd.
发明人： Jochem Gietema , Mohan Mahadevan , Roberto Annunziata , Pieter-jan Reynaert , Elizaveta Ivanova , Yuanwei Li , Tal Shaharabany , Shachar Ben Dayan , Erez Farhan , Francesco Picciotti
CPC分类号： G06V30/41 , G06V30/19013 , G06V30/19173
摘要： 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.
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公开(公告)号：US20230147685A1
公开(公告)日：2023-05-11
申请号：US18084915
申请日：2022-12-20
申请人： Onfido Ltd.
IPC分类号： G06V30/413 , G06V10/25 , G06V10/26
CPC分类号： G06V30/413 , G06V10/25 , G06V10/26
摘要： Described are methods and systems for training a system for detecting anomalies in images of documents in a class of documents. A plurality of training document images of training documents in a class of documents are obtained. For each training document image, the training document image is segmented into a plurality of region of interest (ROI) images, each ROI image corresponding to a respective ROI of the training document. For each ROI image, a plurality of transformations are applied to the ROI image to generate respective transform-specific features for the ROI image and respective transform-specific anomaly scores from the transform-specific features. Based on the respective anomaly scores of the plurality of training document images, a transform-specific threshold is computed for each transformation to separate document images containing an anomaly from document images not containing an anomaly.
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公开(公告)号：US20220351532A1
公开(公告)日：2022-11-03
申请号：US17719199
申请日：2022-04-12
申请人： Onfido Ltd.
发明人： Jochem Gietema , Mohan Mahadevan , Roberto Annunziata , Pieter-jan Reynaert , Elizaveta Ivanova , Yuanwei Li , Tal Shaharabany , Shachar Ben Dayan , Erez Farhan , Francesco Picciotti
摘要： 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.
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公开(公告)号：US20190220660A1
公开(公告)日：2019-07-18
申请号：US16245480
申请日：2019-01-11
申请人： ONFIDO LTD
发明人： Jacques Cali , Peter Roelants , Christos Sagonas , Romain Sabathe
CPC分类号： G06K9/00442 , G06K2209/01
摘要： 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.
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公开(公告)号：US20240205239A1
公开(公告)日：2024-06-20
申请号：US18081119
申请日：2022-12-14
申请人： Onfido Ltd.
CPC分类号： H04L63/1416 , G06V10/764 , G06V10/95 , G06V40/167 , G06V40/171 , G06V40/193 , G06V40/45 , H04L63/0861
摘要： Described herein are computerized methods and systems for detecting fraud during identity verification. An image capture device of a mobile device captures video comprising a plurality of frames of a person's face and transmits the plurality of frames to a server device. The server detects locations of rigid and non-rigid facial features of the person's face in each of the plurality of frames. The server generates time-series signals based upon a position measurement for the facial features in each of the plurality of frames and extracts classification features from the time-series signals. The server applies a trained machine learning classification model to the extracted classification features to generate a fraud detection decision for the plurality of frames.
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