Abstract: A data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a data field. One or more text regions in a selected frame of the plurality of frames are identified. One of the one or more identified text regions that corresponds to a set of attributes associated with the data field are selected. The data of the one of the one or more identified text regions of the selected frame are compared with data of one or more text regions of a subsequent frame. Responsive to determining that the data of the one or more text regions of the subsequent frame is a closer match to the set of attributes, the data of the one of the one or more identified text regions of the selected frame are updated. The data of the one of the one or more identified text regions is then provided to a client device.

Abstract: A data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a data field. One or more text regions in a selected frame of the plurality of frames are identified. One of the one or more identified text regions that corresponds to a set of attributes associated with the data field are selected. The data of the one of the one or more identified text regions of the selected frame are compared with data of one or more text regions of a subsequent frame. Responsive to determining that the data of the one or more text regions of the subsequent frame is a closer match to the set of attributes, the data of the one of the one or more identified text regions of the selected frame are updated. The data of the one of the one or more identified text regions is then provided to a client device.

Abstract: A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation with the frame in a user interface.

Abstract: Systems and methods for enhancing and comparing documents. An example method comprises: comparing document images to identify a first document image of a reference document that corresponds with a second document image of a related document; transforming the second document image based on a layout of the first document image; and performing character recognition of the second document image.

Abstract: Disclosed are systems, methods and computer program products for using prior frame data for OCR processing of frames in video sources to detect natural language text therein. An example includes receiving a frame from a video source and retrieving prior frame data associated with the video source. The OCR-processing includes using prior frame data to detect blobs similar to blobs described in the prior frame data; using detected similar blobs to detect in the frame character candidates similar to character candidates described in the prior frame data; using detected similar character candidates to detect in the frame text candidates similar to text candidates described in the prior frame data; and using detected similar text candidates to detect in the frame text strings similar to text strings described in the prior frame data.

Abstract: A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation with the frame in a user interface.

Abstract: A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation in a user interface.

Abstract: A data capture component of a mobile device receives information for an identification of a data field in a physical document. The data capture component receives a video stream comprising a plurality of frames, wherein each frame comprises a portion of the physical document. A frame is selected from the plurality of frames in the video stream. One or more text regions in the frame are identified. Each of the identified text region(s) in the frame is processed to identify data of each of the identified text region(s) and to select data of one of the identified text region(s) that corresponds to a set of attributes associated with the data field. The selected data is then compared with data of text regions of a subsequent frame. If the data of the text regions of the subsequent frame is a closer match to the set of attributes, the selected data is updated. A display field is then provided with the selected data for presentation in a user interface.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying one or more document images based on its content by determining blocks layout of the document image; recognizing the document image to obtain digital content data representing text content or the potential graphical content of the image; calculating feature values of the document image for features based on the digital content data and the blocks layout; and classifying the document image as belonging to one of document classes based on the calculated feature values.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: Disclosed are systems, methods and computer program products for using prior frame data for OCR processing of frames in video sources to detect natural language text therein. An example includes receiving a frame from a video source and retrieving prior frame data associated with the video source. The OCR-processing includes using prior frame data to detect blobs similar to blobs described in the prior frame data; using detected similar blobs to detect in the frame character candidates similar to character candidates described in the prior frame data; using detected similar character candidates to detect in the frame text candidates similar to text candidates described in the prior frame data; and using detected similar text candidates to detect in the frame text strings similar to text strings described in the prior frame data.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying one or more document images based on its content by determining blocks layout of the document image; recognizing the document image to obtain digital content data representing text content or the potential graphical content of the image; calculating feature values of the document image for features based on the digital content data and the blocks layout; and classifying the document image as belonging to one of document classes based on the calculated feature values.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: Systems and methods for enhancing and comparing documents. An example method comprises: comparing document images to identify a first document image of a reference document that corresponds with a second document image of a related document; transforming the second document image based on a layout of the first document image; and performing character recognition of the second document image.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: Methods and devices are described for detecting boundaries of documents on flatbed and multi-function scanners on a first pass of a carriage assembly, and then performing a high resolution scan on a second pass. High resolution images of documents can then be obtained with little or no interaction normally necessary to identify areas of interest on the scanner bed. Patterns on the scanner cover or lid facilitate not only edge determination, but orientation of text and other objects, and straightening of images in preparation for OCR and related functions. Electronic images and files derived from paper documents may be automatically cropped, deskewed, subjected to OCR, and named consistent with content or other information derived from them.

Abstract: The present invention provides a method of predicting usage of and determining access to a cloud service according to an embodiment of the invention. The method includes the step of monitoring the usage of a service by end users of developers for a predetermined test period. Responsive to statistics associated with the monitoring during the predetermined test period, the method includes determining a future usage payment cost for the developers. Responsive to verification of a unique ID, the method includes performing the service by a service provider.

Abstract: Described herein are methods for determining a type and semi-unique features of electronic files. The methods generally include generating at least one document hypothesis corresponding to the type of the document. For each document hypothesis, the document type is verified. A document type hypothesis is selected. A document name is formed based on the selected document type hypothesis and one or more features of the document. Such steps generally include automatically or programmatically naming of electronic files. A unique or semi-unique name is given, one that reproduces some of the document's contents, attributes and/or characteristics. Each document is provided with a name that can be easily understood and that is related to the content of the document.