| Patent application number | Description | Published |
|---|
| 20090116736 | SYSTEMS AND METHODS TO AUTOMATICALLY CLASSIFY ELECTRONIC DOCUMENTS USING EXTRACTED IMAGE AND TEXT FEATURES AND USING A MACHINE LEARNING SUBSYSTEM - A document analysis system that automatically classifies documents by recognizing in each document distinctive features comprises a document acquisition system, a document recognition training system, a document classification system, a document recognition system, and a job organization system. The document acquisition system receives jobs wherein each job containing at least one electronic document. The document feature recognition system automatically extracts image and text features from each received document. The document classification system automatically classifies recognized electronic documents by finding the best match between the extracted features of each of the document and feature sets associated with each category of document. The document recognition training system automatically trains the feature set for each corresponding category of documents, wherein the training system using extracted features of unrecognized documents automatically modifies the feature set for a document category. The job organization system automatically organizes each job according to the document categories it contains. | 05-07-2009 |
| 20090116746 | SYSTEMS AND METHODS FOR PARALLEL PROCESSING OF DOCUMENT RECOGNITION AND CLASSIFICATION USING EXTRACTED IMAGE AND TEXT FEATURES - A method of parallel processing jobs received from a plurality of users by a document analysis system that automatically classifies documents to organize each job, automatically separates each job into its constituent electronic document and automatically separate the document into subsets of electronic pages. For each page of each subset, the method automatically extracts image features that are indicative of how the document is laid out or textually-organized. For each subset, the method automatically compares the extracted features with feature sets associated with each document category to determine a comparison score for the subset. The method then classifies the electronic document as being one of the categories of documents using the comparison score for each of the subsets and organize the job according to the categories of documents the job contains. | 05-07-2009 |
| 20090116755 | SYSTEMS AND METHODS FOR ENABLING MANUAL CLASSIFICATION OF UNRECOGNIZED DOCUMENTS TO COMPLETE WORKFLOW FOR ELECTRONIC JOBS AND TO ASSIST MACHINE LEARNING OF A RECOGNITION SYSTEM USING AUTOMATICALLY EXTRACTED FEATURES OF UNRECOGNIZED DOCUMENTS - A method in a document analysis system automatically extracts image and text features from each received electronic document and compares the extracted features with feature sets associated with each category of document to determine whether the document is recognizable as belonging to a document category. If an electronic document is recognized as belonging to one of the document categories, the method classifies the electronic document as belonging to that document category. If, however, an electronic document is unrecognized, the method submits the unrecognized document to a learning phase, in which the unrecognized document is presented to a human trainer for manual classification of the unrecognized electronic document into a document category, and automatically modifies at least one of the features and the weights of the feature set of the document category corresponding to the manually-classified electronic document using the automatically extracted features of the manually-classified document. | 05-07-2009 |
| 20090116756 | SYSTEMS AND METHODS FOR TRAINING A DOCUMENT CLASSIFICATION SYSTEM USING DOCUMENTS FROM A PLURALITY OF USERS - A method of training a document analysis system that automatically extracts image and text features from each received electronic document and compares the extracted features with feature sets associated with each document category is provided. If an electronic document is recognized as belonging to one of the document categories with predetermined confidence, the method classifies the electronic document as being of that one document category. If an electronic document is not recognized as belonging to one of the document categories with predetermined confidence, however, the method submits the unrecognized document to a training phase in which the document is recognized as belonging to a document category and automatically modifies at least one of the features and the weights of the features of the feature set for the document category for the now-recognized document. | 05-07-2009 |
| 20090119296 | SYSTEMS AND METHODS FOR HANDLING AND DISTINGUISHING BINARIZED, BACKGROUND ARTIFACTS IN THE VICINITY OF DOCUMENT TEXT AND IMAGE FEATURES INDICATIVE OF A DOCUMENT CATEGORY - A method of enhancing electronic documents received from a plurality of users by a document analysis system for improving automatic recognition and classification of the received electronic documents, is provided. For each page of a received electronic document, the method filters the page to infer binarized-background artifacts resulting from the binarization of the original grayscale or color image source document and which reside in the vicinity of binarized text and binarized image features in the page, so that the binarized text and binarized images may be distinguished from the binarized-background artifacts and extracted from the document. The method then uses the extracted features from the filtered document to automatically recognized and classify a document into a document category. | 05-07-2009 |
| Patent application number | Description | Published |
|---|
| 20080298583 | System and method of quantum encryption - The present invention relates to a crypto-system. According to one embodiment, the crypto-system includes a key synchronizer and/or cryptographic circuitry. The key synchronizer is configured to synchronize a cryptographic key stream with another communication entity using polarized photons. The cryptographic circuitry is configured to generate cipher text from plain text and/or plain text from cipher text, based on the synchronized key stream. | 12-04-2008 |
| 20080298584 | Variable length private key generator and method thereof - The present invention relates to a variable length private key generator. According to one embodiment, the variable length private key generator includes a permuter. The permuter is configured to generate a key stream of a desired length by permuting a plurality of shift registers. The permuter includes the plurality of shift registers, a plurality of clocking modules, and/or an output module. Each clocking module corresponds to a different one of the plurality of shift registers and is configured to generate a clocking signal based on selected bits of the corresponding shift register. The output module is configured to output the key stream based on at least one clocking signal and output of at least one of the plurality of shift registers. | 12-04-2008 |
| 20090103726 | Dual-mode variable key length cryptography system - In a cryptography system, client and server terminals each generate a private key constituting a randomized compilation of dynamic system parameters. Public keys are then generated based on the private keys, exchanged between the terminals, and used to generate a shared secret. Key stream generators generate a randomized key stream at each terminal using the shared secret, based on self-generating primitive polynomials. Key length is user selected, and may be modified during an ongoing encryption session. The generator includes a plurality of linear feedback shift registers whose lengths are self-configuring based on the user-specified key length. The registers are interconnected so that their output, namely, the key stream, is non-linear and random. Data is converted to binary form and encrypted by XOR'ing the binary-format data with the key stream. The system may be used in both a static secure transfer mode and a dynamic secure real time transfer mode. | 04-23-2009 |
