151results about "Signature reading/verifying" patented technology

A system and a method for verifying authenticity of a physical copy and a digital copy of a document are disclosed. The method comprises registering a document in a repository by storing details related to the document in a location of the repository. A symbology for the document is generated. The symbology is an identifier of the location of the repository comprising the document. The symbology is associated with either a physical or a digital copy of the document. The digital copy of the document is printed to generate a printed copy. The printed copy or the physical copy of the document is scanned to generate a scanned image. The document and the details related to the document present at the location of the repository are accessed. The scanned image is compared with the document stored in the repository to determine the authenticity of either the physical copy or the digital copy of the document.

The invention relates to the technical field of information security, and discloses a handwriting dynamic encryption and electronic signature method based on a national secret algorithm, and the method comprises the steps: obtaining the handwriting data of a user, and carrying out the preprocessing of the data to remove noise and errors; carrying out feature extraction on the preprocessed handwriting data, extracting corresponding track features, speed features and pressure features, and generating a feature hash value of a unique identifier through a cryptographic SM3 hash algorithm; splicing and combining the feature hash value and a user private key, deriving a dynamic key through a national secret SM2 algorithm, and generating an electronic signature by using the dynamic key; an electronic signature is combined with a timestamp to form a structured signature packet, and the signature packet is hierarchically encrypted and stored in a database through a national cryptographic SM4 algorithm. According to the method and the system, the handwritten signature picture, the digital signature technology, the electronic signature technology and the biological recognition and layout file processing technology are fused, so that the safety and the reliability of electronic document signing are improved.

The present disclosure provides a character recognition model training method and apparatus, a character recognition method and apparatus, a device and a medium, relating to the technical field of artificial intelligence, and specifically to the technical fields of deep learning, image processing and computer vision, which can be applied to scenarios such as character detection and recognition technology. The specific implementing solution is: partitioning an untagged training sample into at least two sub-sample images; dividing the at least two sub-sample images into a first training set and a second training set; where the first training set includes a first sub-sample image with a visible attribute, and the second training set includes a second sub-sample image with an invisible attribute; performing self-supervised training on a to-be-trained encoder by taking the second training set as a tag of the first training set, to obtain a target encoder.

Aspects of the embodiments described herein are related to systems, methods, and computer products for performing automatic check fraud detection. Aspects of embodiments described herein provide artificial intelligence systems and methods that analyze an image of an incoming check, compare the features of the image to the associated features on a reference check, and generate a check fraud score based on the comparison, and either approve the incoming check or flag the incoming check for manual review.

Systems, apparatuses, methods, and computer program products are disclosed for providing continuous signature management. An example method includes detecting, by an event identification circuitry, a user authentication event and receiving, by communications hardware, a signature from the user during the user authentication event. The example method further includes determining, by the event identification circuitry, a signature parameter set for the signature and determining, by the event identification circuitry, whether the user authentication event corresponds to an authentic event type. The example method further includes in an instance in which the user authentication event corresponds to the authentic event type, storing, by signature management circuitry, the signature and corresponding signature parameter set in a signature profile associated with the user within a signature corpus.

Disclosed herein are computer-implemented method, system, and computer-readable medium embodiments for providing a virtual second image during remote deposit of documents. A system generates, from a field of view of a camera, a live stream of image data comprising imagery of a portion of the document. The system obtains, via an optical character recognition program, one or more data elements from the imagery of the portion of the document and generates a first image of a front side of the document. The system receives an electronic signature of a customer via a user interface and, upon verifying the electronic signature, generates a virtual second image by merging the electronic signature with a second image for a back side of the document selected from a plurality of back images. The system transmits the first image, the virtual second image, and the one or more data elements to a remote deposit platform.

The invention relates to the technical field of risk assessment, in particular to a bill risk assessment method and system for a bill comprehensive management platform based on artificial intelligence, and the method comprises the following steps: positioning and recognizing bill information based on image edge features and field anchor points, verifying identity consistency, constructing a role path chain, and verifying a circulation logic relation. And marking behavior anomalies and paths. According to the method, stable structure reference points are extracted through image edge ink mark concentration changes, tilt correction and size adjustment are carried out, accurate positioning of a field area is achieved in combination with a field anchor point proportion, structured information extraction and field content recognition are achieved, and character consistency judgment and seal superposition degree matching are combined to execute identity verification. Through verification of a node sequence and a role evolution path logic relation, identification of abnormal behaviors in a transaction path is realized, identity consistency is verified, transaction chain rationality is evaluated, and risk identification granularity and path behavior abnormity determination precision are improved.

The embodiment of the invention discloses a handwriting image identification method and system based on artificial intelligence, and the method comprises the steps: firstly collecting a to-be-identified handwriting image and a known sample handwriting image, and generating a target handwriting image set; sequentially performing stroke region segmentation, stroke feature extraction and texture mode analysis on the handwriting images in the set to generate a mixed feature data set containing a traditional handwriting feature set and a deep learning handwriting feature set; inputting the mixed feature data set into a Triplet network model, and generating a first discriminative feature vector of the to-be-identified handwriting image and a second discriminative feature vector of a known sample handwriting image through triple loss function joint optimization training; and finally, generating a handwriting image identification report containing the feature matching score and the author affiliation probability based on the first discriminative feature vector and the second discriminative feature vector. The accuracy and reliability of handwriting identification are improved.

To perform learning quickly with a small amount of training data and to verify signatures with high accuracy.SOLUTION: A signature verification system is as described in the following. An image containing one or more handwritten characters is divided into a plurality of patches of a predetermined size for each character. For each of the divided patches, an embedding feature, which is data representing pixel and positional features of the patch, is calculated. Based on the calculated embedding features of each patch, the type of each patch is identified, and based on the identified patch types and the positions of the patches, a context of each patch in the image is calculated. A discrete representation model that applies an attention mechanism, MSA, to the overall embedding features is stored. A signature verification model is provided, which receives, as input, two images each containing one or more handwritten characters and outputs a probability that the two input images are images of characters written by the same writer. A new signature verification model is generated by replacing a part of the signature verification model with the discrete representation model.SELECTED DRAWING: Figure 4

The invention provides a multi-model signature matching method and device, a storage medium and a program product, and relates to the technical field of text recognition. The multi-model signature matching method comprises the following steps: preprocessing a signature image; extracting a feature vector of the signature image; performing OCR model and multi-modal large model identification on the signature image; performing similarity value calculation on the vector of the signature image and the stock vector; and the similarity values between the vectors and the recognition results of the OCR model and the multi-modal large model are integrated to be matched, and a final result is obtained. According to the method, the feature extraction model, the OCR model and the multi-modal large model are used, and the results of various models are combined according to a certain algorithm, so that the matching precision of signature images such as poor signature images and fuzzy signature images is effectively improved.

The invention discloses a signature handwriting authenticity digital identification method based on multi-modal features, and relates to the technical field of image processing, and the method comprises the following specific steps: 1, obtaining off-line image data and on-line time sequence data of two groups of signatures to be identified, the data preprocessing module carries out standardization processing on the offline image data and the online time sequence data of the signature to be identified to obtain preprocessed offline image data and preprocessed online time sequence data; 2, inputting the preprocessed offline image data into an offline feature extraction network, and extracting and outputting 1024-dimensional offline features; and 3, inputting the preprocessed online time sequence data into an online signature feature extraction network. According to the method, the online features and the offline features of the signature handwriting are fused and combined to form multi-mode signature handwriting digital recognition, the subtle difference of the counterfeited signature handwriting in static structure consistency and dynamic behavior consistency can be effectively captured, and the recognition capability of complex counterfeited means is remarkably improved.

The invention provides a character recognition management method and system fusing multi-modal data, and relates to the technical field of data processing, and the method comprises the steps: continuously capturing heterogeneous multi-source unsteady business instruction sequences submitted by employees; based on the heterogeneous multi-source unsteady service instruction sequence, executing a tensor reconstruction operation of an embedded space through a cross-modal depth feature alignment network, and outputting a structured high-dimensional tensor of a dimension specification; and based on the structured high-dimensional tensor, performing homogenized set division by using a K-means clustering algorithm driven by feature similarity to generate a feature set cluster with a compact feature. According to the invention, efficient management of text information in a banking business scene is realized.

The invention belongs to the field of image recognition and processing, particularly relates to a handwritten signature set construction method and system based on a protocol and computer equipment, and aims to solve the problem of how to improve the construction efficiency of a handwritten signature data set. The method comprises the following steps: performing text content identification on a protocol image file to obtain a text region block, a position of the text region block, and characters and character positions in the text region block; extracting characters in the text region blocks and splicing the characters to obtain text content; identifying a printed name and a handwritten signature in the text content, and matching the printed name with the handwritten signature to obtain a name pair set; and traversing and verifying the name pair set to obtain a labeling result of the handwritten signature. According to the method, the whole process automation of handwritten signature recognition, verification and labeling is realized, and the efficiency and accuracy of handwritten signature set construction are improved.

The application discloses a kind of doctoral and master degree thesis authorization page identification method, comprising: extracting electronic version degree thesis by page to form image set to be examined;According to the image set to be examined, paper version degree thesis is scanned to generate image set to be examined;Image set to be examined is sent into authorization page identification classifier, it is judged whether there is authorization page;If not, output the conclusion without authorization page, if there is, then execute next step;Handwritten signature of author or tutor is detected in authorization page;Output authorization page automatic detection result.The application converts effective authorization page into image classification and target detection problem by automatic detection, and realizes the automatic detection of authorization page and the automatic discrimination of whether authorization page is effective by using image classification and target detection technology based on deep convolution network.

The present invention relates to the technical field of government information data security management, and specifically to a security management system and method for government information data based on big data. The present invention monitors the storage status parameters of various data storage terminals of government agencies, calculates a transfer pressure index, and compares it in combination with preset double thresholds. When the transfer pressure index exceeds the upper limit, a forced transfer instruction is automatically triggered, and semantic analysis is combined to identify transferable and non-transferable files. The use status evaluation value of the transferable files is further calculated, and the files are divided into positive demand files and non-demand files. The positive demand files are determined to be transmitted to the corresponding demand storage area according to the demand status evaluation value, and the non-demand files are determined to be transmitted to the corresponding important storage area according to the important status evaluation value. At the same time, the transmission of the files to be stored is encrypted and managed, thereby realizing dynamic adjustment and security management of government data and improving resource utilization and data security.

The invention provides a non-contact double-recording signature method and device based on end intelligence, and the method comprises the steps: loading a face recognition model and a gesture recognition model preset in end side equipment, and initializing a real-time video stream of a camera; face detection, living body judgment and facial feature comparison are carried out based on the real-time video stream, and an identity verification result is generated; synchronously recognizing a gesture of a user or an object moving track, matching a standard signature template through dynamic time warping, and generating a track consistency verification result; the identity verification result, the track consistency verification result and the signature track data are locally encrypted and stored, and are asynchronously uploaded to a server when the network is recovered; and through a timestamp alignment mechanism, audio and video streams in a signature process, an identity verification result and track data are synchronously recorded, encrypted and stored. According to the invention, the authenticity and security of signature are effectively improved, the risk of data leakage is reduced, and the system stability is enhanced.

The invention provides a title review process management method and system, and relates to the technical field of review process management, and the method comprises the steps: constructing a database for storing historical review features, obtaining to-be-reviewed data, extracting the features of the to-be-reviewed data to obtain to-be-reviewed features, and carrying out the preliminary review through a preset review rule to obtain a preliminary review result; if the preliminary review result conforms to the expectation, calculating a first similarity between the to-be-reviewed feature and a working class sub-feature in the historical review feature, and if the preliminary review result does not conform to the expectation, sending out a material doubt signal; and judging whether the first similarity is greater than a first preset similarity threshold and less than 1, if so, sending a material doubt signal, and otherwise, sending a material legal signal. The review efficiency can be improved.

A mail signature verification system employs a software that is configured to remove pixels of a digital photograph taken of a signature through an opaque security window. The mail piece can be signed and then the signature is covered with the signature cover having a security window therein. The signature reading station of a mail processing machine compresses the security window against a press plate and illuminates the signature with a light element while taking the digital photograph. The software then analyzes the digital photograph to remove pixels having a grey scale value below an upper grey scale threshold and remove pixels above a lower grey scale threshold, thereby rendering a signature with these darkest of pixels over the lightest of pixels.

An example electronic apparatus includes a user interface device, a communication device, a processor, and a memory to store instructions executable by the processor. The processor is to execute the instructions to obtain an image regarding a document including handwritten text, distinguish a writer who writes the handwritten text based on feature information of the handwritten text that is read from the image, and generate a file regarding the document based on at least one of setting information of the writer or setting information of the handwritten text.

The application relates to the technical field of image matching, in particular to a handwritten data double-track recording system and recording equipment capable of preventing tampering and easy tracing, which comprises an image acquisition module, a paper handwriting extraction module, a key point evaluation module and a handwriting security evaluation module.

According to the inspection and detection qualification intelligent approval method based on multi-modal semantic understanding and block chain evidence storage provided by the invention, a four-in-one technical architecture of semantic understanding, credible consensus, intelligent decision making and judicial evidence storage is constructed; through four key steps of dynamic knowledge graph construction, multi-modal material analysis, cross-chain multi-node collaborative approval and whole-process block chain evidence storage, intelligent and reliable inspection and detection qualification approval can be realized.

The application discloses a pen tip tracking method, medium and computing device, wherein the method comprises: acquiring a pen operation video; acquiring a template image from the pen operation video by using a specific detection model, the template image comprising a pen tip to be tracked, the specific detection model being trained based on a training sample set comprising a plurality of different pen tip images; and determining a pen tip position in the pen operation video based on the template image, the pen operation video and a tracking model constructed based on a twin network. The pen tip tracking method can not only accurately identify pen tip images in pen operation videos in different environments, but also effectively improve the ability of the tracking task to resist the influence of shooting conditions such as light and shadow, while ensuring the robustness, real-time performance and accuracy of the tracking task.

The invention relates to an electronic certificate file detection method, and belongs to the field of data processing. Comprising the following steps: configuring a certificate file detection standard; rapidly detecting the OFD format; extracting OFD file information, and constructing an information association relationship: analyzing the license file based on a standard, realizing automatic extraction of an electronic license OFD file directory structure and an XML node relationship, and constructing an OFD analysis engine; oFD file information detection: carrying out OFD file information verification based on a certificate file detection standard configured by a user, an OFD file information extraction result and certificate information in an electronic certificate library; oFD file layout detection: detecting the layout of the certificate file based on a certificate file detection standard configured by a user and an OFD file information extraction result; detecting signature information; and visual feedback is realized. The OFD file internal data verification blank is filled, an OFD format detection framework is constructed, the tampering recognition rate is high, and the efficiency is high.

Disclosed embodiments can pertain to utilizing biometric behavior to prevent inappropriate entry of sensitive information. Current biometric behavior of a user, specific to the user's interaction with an electronic form, can be acquired and compared to benchmark biometric behavior of the user associated with past interaction with the electronic form to create a comparison result. A similarity score based on the comparison result can then be established. It can be inferred that sensitive information was incorrectly entered into the electronic form when the similarity score satisfies a predetermined similarity threshold. The sensitive information can be identified, and a machine learning model can be triggered to generate a risk score based on the similarity score and the identified sensitive information. A user can be prompted to redact incorrectly entered sensitive information when the risk score satisfies a predetermined risk threshold.

Various embodiments herein each include at least one of systems, methods, and software for identity verification. Some such embodiments identify a user based on analysis of their handwriting. Some such embodiments may be utilized to authenticate an individual, for emergency authentication or when other authentication solutions are not available, as one of a two or more step authentication process, authenticating checks, authenticating a signature or other handwriting on another document, and the like. One embodiment, in the form of a method, includes storing a set of handwriting characteristics of an individual identified during processing of a plurality of handwriting samples of the individual. The method may then determine whether an input handwriting sample is handwriting of the individual based on the stored set of handwriting characteristics of the individual and then output a result of the determining.

The invention discloses a legal document fall positioning and quality inspection method and device based on semantic understanding, and relates to the technical field of legal review, and the method comprises the steps: analyzing electronic document data, extracting text content, associating the text content with corresponding coordinate metadata, and generating multi-modal document data; performing deep semantic and structural analysis on the multi-modal document data, extracting a text sequence, executing natural language analysis and semantic analysis, obtaining a phrase role labeling result, judging a termination position, and obtaining a semantic boundary; based on the semantic boundary and the coordinate metadata, performing retrieval positioning on the multi-modal document data, extracting coordinate text data and page evidence image segments, obtaining a structured entity and segmented signature blocks through entity recognition and signature detection, and constructing a signature element map; according to the method, automatic verification and accurate fund positioning of the document are realized, the processing efficiency is improved, manual intervention is reduced, and the method is widely applicable to automatic examination and compliance inspection of the electronic document.

The application provides an electronic signature method, system, device and storage medium based on multiple verifications, and the method comprises the following steps: a mobile terminal receives a request of a user for generating an electronic signature; electronic signature currently signed by the user and signature related information in the signing process are collected; storage address information is generated according to at least the pattern information of the current electronic signature and the signature related information; and at least the pattern information and the storage address information are uploaded to a block chain node. The application can confirm that the signatory is the person himself through multiple verifications, and can protect the signature information from being lost and being tampered with through the block chain technology, thereby improving the authentication security.

The invention provides a multi-modal handwritten signature verification method based on global features, which comprises the following global feature extraction steps of a multi-modal handwritten signature: S1, collecting multiple modal data of a handwritten electronic signature of a user, including a signature image pic and a signature time sequence seq; wherein the time sequence at least comprises three physical characteristics (i = 1, 2, 3,..., T) of an abscissa sequence {xi}, an ordinate sequence {yi} and a pressure sequence {pi}, and T is total time; s2, extracting global features from the signature image and the time sequence at the same time, and splicing the global features to form a handwritten electronic signature feature vector; for the signature image, the obtained features comprise a signature area A, a height H = ymax-ymin, a width W = xmax-xmin, an aspect ratio H / W, a gravity center Cx = Sigma ixipi / Sigma ixi, and Cy = Sigma iyipi / Sigma iyi.