1770 results about "Optical character recognition" patented technology

An intelligent document recognition-based document management system includes modules for image capture, image enhancement, image identification, optical character recognition, data extraction and quality assurance. The system captures data from electronic documents as diverse as facsimile images, scanned images and images from document management systems. It processes these images and presents the data in, for example, a standard XML format. The document management system processes both structured document images (ones which have a standard format) and unstructured document images (ones which do not have a standard format). The system can extract images directly from a facsimile machine, a scanner or a document management system for processing.

A device for switching between code-based searching, optical character recognition (OCR) searching and visual searching is provided. The device includes a media content input for receiving media content from a camera or other element of the device and transferring this media content to a switch. Additionally, the device includes a meta-information input capable of receiving meta-information from an element of the device and transferring the meta-information to the switch. The switch is able to utilize the received media content and the meta-information to select and/or switch between a visual search algorithm, an OCR algorithm and a code-based algorithm.

A system for managing documents, comprising: interfaces to a user interface, proving an application programming interface, a database of document images, a remote server, configured to communicate a text representation of the document from the optical character recognition engine to the report server, and to receive from the remote server a classification of the document; and logic configured to receive commands from the user interface, and to apply the classifications received from the remote server to the document images through the interface to the database. A corresponding method is also provided.

A pure adversarial optical character recognition (OCR) approach in identifying text content in images. An image and a search term are input to a pure adversarial OCR module, which searches the image for presence of the search term. The image may be extracted from an email by an email processing engine. The OCR module may split the image into several character-blocks that each has a reasonable probability of containing a character (e.g., an ASCII character). The OCR module may form a sequence of blocks that represent a candidate match to the search term and calculate the similarity of the candidate sequence to the search term. The OCR module may be configured to output whether or not the search term is found in the image and, if applicable, the location of the search term in the image.

The systems and methods of the client agent describe herein provides a solution to obtaining, recognizing and taking an action on text displayed by an application that is performed in a non-intrusive and application agnostic manner. In response to detecting idle activity of a cursor on the screen, the client agent captures a portion of the screen relative to the position of the cursor. The portion of the screen may include a textual element having text, such as a telephone number or other contact information. The client agent calculates a desired or predetermined scanning area based on the default fonts and screen resolution as well as the cursor position. The client agent performs optical character recognition on the captured image to determine any recognized text. By performing pattern matching on the recognized text, the client agent determines if the text has a format or content matching a desired pattern, such as phone number. In response to determining the recognized text corresponds to a desired pattern, the client agent displays a user interface element on the screen near the recognized text. The user interface element may be displayed as an overlay or superimposed to the textual element such that it seamlessly appears integrated with the application. The user interface element is selectable to take an action associated with the recognized text.

A system and method for detecting cheque fraud includes a cheque scanning module and a detection module. The cheque scanning module scans cheques and matches the encoded Magnetic Ink Character Recognition (MICR) data (i.e. serial number, Customer Account Number and amount) from the scanned digital electronic images with items in an issuance database which contains client provided cheque particulars. The detection module passes the cheque images through an optical character recognition (OCR) process to read what is written on the cheque and to match results against the issuance database. If the written information on the face of a cheque is unreadable or there is no match with the information in the issuance database, the detection module passes the cheque through a series of slower more precise OCR processes. Any cheques that are not successfully read and matched are highlighted as an “exception” and immediately forwarded to the client for further action.

A method, system and apparatus for facilitating transcription and captioning of multi-media content are presented. The method, system, and apparatus include automatic multi-media analysis operations that produce information which is presented to an operator as suggestions for spoken words, spoken word timing, caption segmentation, caption playback timing, caption mark-up such as non-spoken cues or speaker identification, caption formatting, and caption placement. Spoken word suggestions are primarily created through an automatic speech recognition operation, but may be enhanced by leveraging other elements of the multi-media content, such as correlated text and imagery by using text extracted with an optical character recognition operation. Also included is an operator interface that allows the operator to efficiently correct any of the aforementioned suggestions. In the case of word suggestions, in addition to best hypothesis word choices being presented to the operator, alternate word choices are presented for quick selection via the operator interface. Ongoing operator corrections can be leveraged to improve the remaining suggestions. Additionally, an automatic multi-media playback control capability further assists the operator during the correction process.

The apparatus and method of the invention relate to data entry and menu selection. Applications include: (a) data entry for ideographic languages, including Chinese, Japanese and Korean; (b) fast food ordering; (c) correction of documents generated by optical character recognition; and (d) computer access and speech synthesis by persons temporarily or permanently lacking normal motor capabilities. In a preferred embodiment, each option of a menu is associated respectively with a selectable region displayed adjacent an edge of a display, forming a perimeter menu and leaving a region in the center of the perimeter menu for the output of an application program. Selectable regions may be on the display, outside the display, or both. A menu option may be selected by clicking on the associated selectable region, by dwelling on it for a selection threshold period or by a cursor path toward the selectable region, or by a combination thereof. Remaining dwell time required to select a selectable region is preferably indicated by the brightness of the selectable region. Submenus of a perimeter menu may also be perimeter menus and the location of a submenu option may be foretold by the appearance of its parent menu option. Menu options may be ideographs sharing a sound, a structure or another characteristic. Ideographs, which may be homophones of one another, may be associated with colored indicating regions and selection of an ideograph may be made by speaking the name of the associated color.

A phishing detection agent is provided. In one embodiment, a user's browser includes a plug-in application or agent that may capture a visual record of a webpage and, with a cached copy of known, authentic websites provided to it via periodic updates, perform a series of image comparison functions to determine if the suspected website is attempting to deceive the user. The phishing detection agent is capable of performing an image recognition algorithm, such as logo recognition algorithm, optical character recognition, an image similarity algorithm, or combination of two or more of the above. If the suspected webpage corresponds to one of the authentic web pages, but the domain name of the suspected web page does not match the domain name of one of the authentic web pages, the suspected web page is flagged as a phishing web site.

Optical character recognition (OCR) for images such as a street scene image is generally a difficult problem because of the variety of fonts, styles, colors, sizes, orientations, occlusions and partial occlusions that can be observed in the textual content of such scenes. However, a database query can provide useful information that can assist the OCR process. For instance, a query to a digital mapping database can provide information such as one or more businesses in a vicinity, the street name, and a range of possible addresses. In accordance with an embodiment of the present invention, this mapping information is used as prior information or constraints for an OCR engine that is interpreting the corresponding street scene image, resulting in much greater accuracy of the digital map data provided to the user.

Embodiments herein provide/acquire a document in electronic form (e.g., by receiving, copying, retrieving from storage, scanning combined with optical character recognition, etc.) and receive user input regarding visual impairment. In response to one or more levels of user visual impairment, embodiments herein automatically change (for example, immediately after scanning text) an appearance of the document, without requiring any user input, other than the visual impairment input. More specifically, when changing the appearance of the document, embodiments herein can increase the size of characters in the document, change the contrast or coloring of the text and/or background, and provide text-to-speech conversion of the document, thereby (in one embodiment) producing audio output of the text-to-speech conversion in coordination with a corresponding portion of the document being displayed. When changing the appearance of the document, embodiments herein also reformat the document (e.g., around graphic elements) to accommodate the increased size of the characters.

A system to provide image processing services responsive to requests including image data includes a system layer that forwards a request to an image application processing interface. Image processing provides an image comparison, barcode recognition, and optical character recognition. The image processing compares the image data to products in a database in order to identify a matching product. The system layer receives the matching information and forwards to a user.

A system for extracting and monitoring media tags within video content includes at least one server in communication with a plurality of content sources, the server receiving video content from the content sources, a recorder saving the video content, a detector receiving at least one frame of the video content, the detector detecting one or more unknown text within the frame and creating one or more images, each image associated with one of the one or more unknown text, the detector generating metadata associated with the one or more unknown text appearing in the frame, and an optical character recognition engine scanning the one or more images and converting the one or more images into one or more known text. The server further determines that the one or more known text is a media tag.

An automated analysis method and tool for a digitally imaged financial item can digitally recognize a plurality of characters across an area of a digital image containing character indicia at predetermined positions in the area and also possibly containing non-character indicia in the area. This finds exemplification in an automated check processing method and check sorting system in which a check's MICR line that has been read and interpreted as invalid can be digitally analyzed, via a digital image of the check, to identify MICR characters that could not be validly read or interpreted by the conventional MICR processing equipment. This includes digitally applying character recognition processing to an invalidated MICR line in a digital image of the financial item (e.g., a check). Previously invalidated MICR line data can then be corrected.

A method for an intelligent identification system to recognize and validate currency base in the uniqueness of their numbers by employing video scanning apparatus in conjunction with optical character recognition (OCR) software and broadcasting capabilities so it can recognize the currency's value from a digitized serial number, store it with or without a “tag”, by memory means and be able to transmit and receive additional lists as a part of a network and as an extension; to recognize foreign countries currency, bank checks, personal checks and bills to be paid, for example: telephone bills, utility bills, etc.

An embodiment of a method for splitting a bill includes displaying a primary bill that includes a plurality of items on a first payer device. A plurality of inputs are received from the first payer device that assign the plurality of items to a first payer and at least one second payer to generate a first secondary bill and at least one second secondary bill. Each at least one second secondary bill is then sent to a respective second payer device, and payments are sent for the first secondary bill from the first payer device and each at least one secondary bill from the respective second payer device. An image of a physical bill may be taken by the first payer device and optical character recognition may be performed on the image to produce the primary bill that is displayed on the display of a first payer device.

Image-based searching for information on a network is provided in response to an image query sent by a user. The image query includes an image captured using a mobile communications device with a camera. The image is processed to detect any text present in the image, and any detected text can be analyzed using a process such as optical character recognition (OCR). The analyzed text is used to search for matches in at least one corresponding domain database, selected from various domain databases present in the network. Thereafter, one or more selected matches and any additional related information can be sent to the user as one or more results for the submitted image query.

A system and method are disclosed which provide a look-down digital imaging device capable of capturing relatively high resolution digital images (e.g., comparable to traditional flatbed scanners). A preferred embodiment provides a look-down digital imaging device comprising a linear sensor for imaging a raster line of an original image placed substantially below the look-down digital imaging device, and a lens for focusing reflected light from the original to such linear sensor. The linear sensor functions much as in traditional flatbed scanners in that it captures a single, congruent digital image of a scanned original. Most preferably, the linear sensor is a high resolution sensor that enables a digital image to be captured having resolution comparable to that of traditional flatbed scanners. For instance, the linear sensor preferably enables capture of a digital image having a resolution no less than approximately 300 dpi. As a result, such linear sensor most preferably captures a digital image having sufficient resolution to permit optical character recognition operations to be performed on such captured image. In a most preferred embodiment, the look-down digital imaging device further comprises a digital video camera for capturing video data of a target scan area. Such video data may be fed in substantially real-time to a display (either included within the look-down digital imaging device or included on a device to which the look-down digital imaging device is coupled), which may aid a user in properly aligning an original within the target scan area.

A system and method for collecting and managing information taken from tokens, like credit cards and gift cards, includes a portable computing device (PCD). The PCD may support a token recognizer that may comprise hardware and/or software that may reside in memory of the PCD. The token recognizer may work in combination with a camera. The token recognizer may comprise a broad recognizer module and an optical character recognition (“OCR”) module. The camera of the PCD may capture images of one or more physical tokens. These captured images of the physical tokens may be processed by the token recognizer so that digital images as well as data provided by the physical tokens may be maintained in memory of the PCD for later presentation to the user. These later presentations on the PCD may be used for account management and for conducting transactions, such as making payment at a point-of-sale (POS) terminal.

An object recognition system comprises a memory for storing a plurality of distance ranges with different distance labels associated with respective distance ranges. The controller converts measured distance values into distance labels according to distance ranges to which the distance values belong. The controller groups the sections or windows of a captured image based on assigned distance labels. Detection area or viewing area of the sensors is divided into a plurality of distance ranges according to tolerance of the measured distance such that broader distance range is defined as the distance from the system is larger. The controller scans the windows with distance labels using a template that defines a joining relationship for the windows and assigns each window with a cluster label that is a combination of the distance label and a occurrence indicia, which is the same for the windows that satisfy the joining relationship. The controller unites the windows having the same cluster labels into a cluster, generates three dimensional data of each of said clusters and combines the clusters that are positioned close to each other based on the three dimensional data to form a candidate of a physical object. The system includes a memory for storing three dimensional data of one or more physical objects that were recognized in previous recognition cycle. The controller infers a physical object which would be recognized in the current cycle based on the stored data and a speed of the vehicle relative to the physical object. The controller compares the inferred physical object with said candidate of a physical object to recognize a physical object.

Systems and methods are provided for processing and extracting content from an image of a driver's license captured using a mobile device. In one embodiment, an image of a driver's license (DL) is captured by a mobile device and corrected to improve the quality of the image. The corrected image is then further processed by cropping the image, identifying the format and layout of the DL, binarizing the image and extracting the content using optical character recognition (OCR). Multiple methods of image cropping may be implemented to accurately assess the borders of the DL, and a secondary layout identification process may be performed to ensure that the content being extracted is properly classified.

A method includes receiving or capturing a digital image using a mobile device, and using a processor of the mobile device to: determine whether an object depicted in the digital image belongs to a particular object class among a plurality of object classes; determine one or more object features of the object based at least in part on the particular object class at least partially in response to determining the object belongs to the particular object class; build or select an extraction model based at least in part on the one or more determined object features; and extract data from the digital image using the extraction model. The extraction model excludes, and/or the extraction process does not utilize, optical character recognition (OCR) techniques. Related systems and computer program products are also disclosed.

This invention provides an infrared illuminator and camera system for imaging of auto vehicle license plates. The system works in ambient light conditions, ranging from bright sunlight, to dim light, to dark, to zero ambient light. It yields high-contrast imaging of the letters and numbers on retro-reflective license plates. The images of the license letter and number combinations can be read manually by a remote operator. They can be converted to text format with optical character recognition computer hardware and software. The text data can then be compared to data files listing license numbers to provide further data about the owner of a licensed vehicle. A decision can be made quickly about whether to allow a vehicle to proceed through a gate, or whether to take other action. The system uses a mono camera that is enhanced for infrared sensitivity and combined with a high power infrared illuminator to maximize range at night, and with shutter speeds set up to capture clear license plate pictures even with fast moving vehicles and even with their headlights on and interfering with human observation of the license plates. Optical filtering to pass infrared in the range of the illuminator and to reduce light outside this range, combines with a lens set up, to avoid vertical smear and sensor overload caused by headlights at night and by highlight reflected glare from the sun in daytime.

A character recognition system is described, in particular a system suitable for use in monitoring cargo container codes or vehicle number plates. An image of the code is first analyzed to extract potential characters. As part of this process, long horizontal and vertical line segments are filtered out. The extracted potential characters are then input to a two-level character recognition means. The first level comprises a neural network classifier that classifies a character into a smaller set of possible characters; and then the second level comprises another neural network classifier which identifies which character among the smaller set of possible characters the extracted character is.