US 2023/0147685 A1 · GENERALIZED ANOMALY DETECTION

Abstract

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.

Claims16

Dependent claims

A computer-implemented method of sourcing training images for a system for detecting anomalies in images of documents in a class of documents, the method comprising:

(a) obtaining one or more document images of a fraudulent document;
(b) for each document image:
(i) segmenting the document image into one or more region of interest (ROI) images, each ROI image corresponding to a respective ROI of the fraudulent document;
(ii) generating a vector representation of each ROI image in an embedding space, the embedding space comprising vector representations of one or more other ROI images from a plurality of sample document images;
(iii) determining a similarity between each ROI image from the fraudulent document and one or more other ROI images from sample document images using the vector representations in the embedding space;
and
(iv) selecting a plurality of sample document images that have ROI images similar to the ROI images from the fraudulent document and generating a training data set using the selected sample document images;
and
(c) training a supervised anomaly detection machine learning model using the training data set.

6 more elements

Dependencies are inferred from the claim text.

Generalized anomaly detection

Life of this patent

Generalized anomaly detection

Life of this patent

Abstract

Claims16