Abstract: A form processing program which is capable of automatically extracting keywords. When the image of a scanned form is entered, a layout recognizer extracts a readout region of the form image, a character recognizer recognizes characters within the readout region. A form logical definition database stores form logical definitions defining strings as keywords according to logical structures which are common to forms of same type. A possible string extractor extracts as possible strings combinations of recognized characters each of which satisfies defined relationships of a string. A linking unit links the possible strings according to positional relationships, and determines a combination of possible strings as keywords.

Abstract: An image processing apparatus includes a command-data storage unit, a handwritten-data recognizing unit, and a matching unit. The command-data storage unit stores therein a command-data table that contains a command character and content of a command corresponding to the command character in an associated manner. The handwritten-data recognizing unit performs character recognition and image analysis on image data to extract handwritten information including a command graphic representing a command with respect to the image data and a command character handwritten near the command graphic. The matching unit matches the command character extracted by the handwritten-data recognizing unit with the command character in the command-data table.

Abstract: Techniques for shape clustering and applications in processing various documents, including an output of an optical character recognition (OCR) process. The output of an OCR process is classified into a plurality of clusters of clip images and a representative image for each cluster is generated to identify clusters whose clip images were incorrectly assigned character codes by the OCR process.

Abstract: A number of regions and partitions may be created based on input handwritten atoms and a grammar parsing framework. Productions for tabular structures may be added to the grammar parsing framework to produce an extended grammar parsing framework. Each of the regions may be searched for a tabular structure. Upon finding a tabular structure, a type of tabular structure may be determined. Configuration partitions may be created, based on the added productions, and added to the created partitions. A set of configuration regions may be created based on the configuration partitions and added to the created regions. The productions for tabular structures and productions of the grammar parsing framework may be applied, as rewriting rules, to the atoms to produce possible recognition results. A best recognition result may be determined and displayed. A mechanism for correcting misrecognition errors, which may occur while recognizing tabular structures, may be provided.

Abstract: A method of compressing a sequence of strokes input at an input device of a processing system is provided in which each stroke input at the input device is represented as a series of digital words representing x and y co-ordinates, a reference co-ordinate of each stroke is expressed in absolute terms, and a co-ordinate other than the reference co-ordinate is expressed as an offset from a preceding co-ordinate by combining a residual error value and an estimate calculated from the previous m co-ordinates using the formula: a ~ n = ? i = 1 m ? ? c i ? a n - i where ci are coefficients selected to model characteristics of the input strokes, and ? represents either an x or a y co-ordinate.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input one or more strokes as digital ink to a processing device. The processing device may produce and present a recognition result, which may include a misrecognized portion. A user may indicate a desire to correct the misrecognized portion and may further select one or more strokes of the misrecognized portion. The processing device may then present the one or more recognition alternates corresponding to the selected one or more strokes of the misrecognized portion. In some embodiments, the processing device may permit a user to rewrite the selected one or more strokes of the misrecognized portion with newly entered digital ink. Features, such as, rewriting and correction of the input digital ink may be discoverable in some embodiments.

Abstract: A printer, scanner device and methods for using same are described herein. A printer device may include a dedicated input that, when actuated, generates and sends a request to a computer for known data or a predetermined print job, e.g., schedule information from a personal information management (PIM) application. A scanner device may include another dedicated input that, when actuated, automatically scans a document fed to the device by the user and sends the scanned image to IM (or other) software on a computer, bypassing the need to manipulate the scanned image using scanner software. The device may be used with printed metapaper, which includes a barcode or other indicia identifying the metapaper and corresponds to a stored template image of the metapaper. When the metapaper is rescanned, the scan can be compared to the stored template information to identify changes and synchronize the changes with the IM software.

Abstract: A wordspotting system and method are disclosed. The method includes receiving a keyword and, for each of a set of typographical fonts, synthesizing a word image based on the keyword. A keyword model is trained based on the synthesized word images and the respective weights for each of the set of typographical fonts. Using the trained keyword model, handwritten word images of a collection of handwritten word images which match the keyword are identified. The weights allow a large set of fonts to be considered, with the weights indicating the relative relevance of each font for modeling a set of handwritten word images.

Abstract: Various technologies and techniques are disclosed for providing bi-handwriting directional handwriting recognition and correction. A combined handwriting recognizer is provided that supports left-to-right and right-to-left language recognition by using a combined dictionary. The combined dictionary includes a dictionary from a language in a first direction, along with a backwards version of a dictionary from a language in a second direction. The combined recognizer is used with the combined dictionary to generate a most likely recognition result for mixed direction hand written input received from a user. Character by character correction is provided for mixed left-to-right and right-to-left text. The most likely recognition result is displayed in a visual order. The user can correct a particular character to a different character. When recognized text needs to be sent to a separate application, an inverse bi-directional process is performed to convert the text from the visual order to the logical order.

Abstract: Script detection service techniques are described. In an implementation, a determination is made as to which human writing system is associated with individual text characters in a string of one or more text characters based on values representing the individual text characters in the string. A particular human writing system is designated as associated with the string based on the values associated with the individual text characters in the string.

Abstract: A character recognition device which recognizes an operation for writing a character performed by a housing including an acceleration sensor 7 while being moved in a spatial plane based on a measurement result from the acceleration sensor, a control section 1 acquires acceleration data of each component acquired during the period from the start of writing to the end of the writing of one character determined based on acceleration data of a component associated with each axis of the acceleration sensor, as a series of acceleration data that are temporally continuous from the first stroke to the last stroke of the character including acceleration between strokes. The control section identifies feature points for each component that exist in a series of acceleration data, generates feature point data for each component which includes the plurality of feature points as inputted character data, and collates it with basic character data.

Abstract: System for implementing user handwriting according to the present invention, comprising : a handwriting input module (120) for receiving user handwriting including at least 100 to 200 characters by a user with sample sentences; a feature determining module (150); a distance determining module (160) for determining a vertical distance between an uppermost point mark and a lowermost point mark between 2 characters and their segments and a horizontal distance between a leftmost point mark and a rightmost point mark between 2 characters and their segments; a position determining module (170) for determining positions of the uppermost and lowermost point marks and the leftmost and rightmost point marks between 2 characters and their segments; a handwriting combining module (180) for combining several handwriting base on data recognized by the feature determining module (150), the distance determining module (160) and the position determining module (170); and a handwriting output module (200) for outputting handwr

Abstract: Techniques for recognizing discrete multi-component symbolic input from a user can be applied to, for example, handwriting or speech. The techniques can include providing a database of model input sequences, where each model input sequence corresponds to a symbol to be recognized. Input functions, for example, discrete strokes, are obtained from a user and segmented into a sequence of discrete components. Hypothesis symbol sequences are obtained by comparing the discrete components to a database of symbols to be recognized and updating hypothesis symbol sequences based on the results of the comparison and hypothesis symbol sequence history from input previously acquired in time.

Abstract: An apparatus (100) for handwriting recognition has a touch-sensitive display screen (240) providing a hand writing input area (270) capable of detecting hand-made user input. The apparatus also has a processing device (300) coupled to the touch-sensitive display screen and providing a user interface to a user. The handwriting input area (270) includes a writing start area (280) capable of switching between a first two-dimensional scope (282) and a second two-dimensional scope (282?), larger than the first two-dimensional scope. The processing device (300) is configured to handle said handmade user input as either a logical mouse event, associated with a control operation for said user interface, or a logical pen event, associated with handwriting.

Abstract: Techniques described herein may recognize handwritten characters that are written at least partially over the top of one another that are input to a computing device. The handwritten characters may be formed of one or more strokes. A user may write characters or parts of words over approximately the same area of graphical user interface (i.e., on top of each other) without having to wait for a timeout between character input and without having to select a button or provide another input indicating the character is complete before entering input for another character. Once a character is at least partially recognized, a graphical indication corresponding to the user input displayed on a screen may be altered. Such alterations may include fading or changing size or location of the graphical indication.

Abstract: A method for analyzing image identifications to determine whether image identifications identify an entity (e.g., license plate of a vehicle). Identification sets are received from at least one optical character recognition (OCR) engine. Each identification set includes a character string and an associated confidence level. Each character string is derived by the respective OCR engine from an image of the entity. An identification set is received from each OCR engine. The character strings are compared, resulting in identifying all conflicting character strings, wherein any two non-identical character strings are considered to be conflicting. The confidence level in each identification set is analyzed, resulting in determining whether each confidence level exceeds a predefined threshold confidence level. At least one rule is applied to the preceding results to ascertain whether or not the entity has been identified. An indication of whether or not the entity has been identified is stored.

Abstract: Techniques described herein may recognize handwritten characters that are written at least partially over the top of one another that are input to a computing device. The handwritten characters may be formed of one or more strokes. A user may write characters or parts of words over approximately the same area of graphical user interface (i.e., on top of each other) without having to wait for a timeout between character input and without having to select a button or provide another input indicating the character is complete before entering input for another character. Once a character is at least partially recognized, a graphical indication corresponding to the user input displayed on a screen may be altered. Such alterations may include fading or changing size or location of the graphical indication.

Abstract: Described is searching directly based on digital ink input to provide a result set of one or more items. Digital ink input (e.g., a handwritten character, sketched shape, gesture, drawing picture) is provided to a search engine and interpreted thereby, with a search result (or results) returned. Different kinds of digital ink can be used as search input without changing modes. The search engine includes a unified digital ink recognizer that recognizes digital ink as a character or another type of digital ink. When the recognition result is a character, the character may be used in a keyword search to find one or more corresponding non-character items, e.g., from a data store. When the recognition result is a non-character item, the non-character item is provided as the result, without keyword searching. The search result may appear as one or more item representations, such as in a user interface result panel.

Abstract: A system for determining the orientation of digital ink is provided having a sensing pen and a processor. The system measures the orientation of the pen during writing by the pen on a surface printed with tags. Each tag encodes data on an identity of the surface associated with a digital description of the surface and on the respective location of that tag on the surface. The digital ink is generated by associating the digital description with the data encoded by the tags sensed by the pen during said writing. The orientation of the digital ink is determined using the measured orientation of the pen.

Abstract: The present invention discloses a method for recognizing a handwritten character, which includes the following steps of: obtaining a coarse classification template and a fine classification template; receiving a handwritten character input signal from a user, gathering a discrete coordinate sequence of trajectory points of the inputted character, and pre-processing the discrete coordinate sequence; extracting eigenvalues and calculating a multi-dimensional eigenvector of the inputted character; matching the inputted character with the coarse classification template to select a plurality of the most similar candidate character classes; and matching the eigen-transformed inputted character with sample centers of the candidate character classes selected from the fine classification template, and determining the most similar character classes among the candidate character classes. The present invention further discloses a system for recognizing a handwritten character.

Abstract: Methods and systems for providing navigation assistance on a mobile device are provided. A method may include analyzing handwriting data to recognize one or more objects depicted in the handwriting data. The method may further include determining if one or more applications are associated with the handwriting data based on the one or more objects recognized in the handwriting data. If one application is determined to be associated with the handwriting data, the one application may be launched. If two or more applications are determined to be associated with the handwriting data, information allowing a user to select an application to launch from the two or more applications may be displayed.

Abstract: Described is a bimodal data input technology by which handwriting recognition results are combined with speech recognition results to improve overall recognition accuracy. Handwriting data and speech data corresponding to mathematical symbols are received and processed (including being recognized) into respective graphs. A fusion mechanism uses the speech graph to enhance the handwriting graph, e.g., to better distinguish between similar handwritten symbols that are often misrecognized. The graphs include nodes representing symbols, and arcs between the nodes representing probability scores. When arcs in the first and second graphs are determined to match one another, such as aligned in time and associated with corresponding symbols, the probability score in the second graph for that arc is used to adjust the matching probability score in the first graph. Normalization and smoothing may be performed to correspond the graphs to one another and to control the influence of one graph on the other.

Abstract: The present invention relates to an apparatus and methods for performing image restoration. More specifically, the present invention relates to an apparatus and methods which are capable of quickly restoring various sizes of selected areas of an image. In one embodiment, a user may select or mark a target region in an image which is to be restored. A source window may then be generated and a pixel from within the target region may be selected for restoration. The intensity distribution of pixels surrounding the selected pixel may be compared with other pixels in the image and a pixel to be used for restoration of the selected pixel may be chosen based on the comparison of the intensity distributions. Once a pixel is chosen for restoration, the selected pixel and its surrounding pixels may be restored using the intensity distribution of the chosen pixel and its surrounding pixels. The method may continue in this manner until all pixels within the target region have been restored.

Abstract: Systems and methods for use in handwriting recognition in computer algebra are provided. One disclosed method includes receiving handwriting input from a user via a handwriting input device, the handwriting input representing a mathematical expression. The method further includes, at a recognizer, processing the handwriting input to recognize a plurality of candidates and ranking the plurality of candidates to form initial candidate data. The method may further include, at an application program, scanning the plurality of candidates for segments that match application-level criteria, and adjusting a rank of one or more of the plurality of candidates based on the matching, to form a processed candidate list. The method may further include displaying the processed candidate list via a graphical user interface.

Abstract: Apparatuses, methods, and computer-storage media provide character string templates to facilitate receiving non-prose handwriting input from a user and converting that input to text to create character strings capable of being provided to application and/or displayed to the user. Templates may be provided manually or automatically, and may or may not be associated with an application text box. A template generally contains pre-populated segments and open segments for receiving handwriting.

Abstract: The disclosed architecture is a new feature extraction approach to handwriting recognition. Given an handwriting sample (e.g., from an online source), a sequence of time-ordered dominant points are extracted, which include stroke-endings, points corresponding to local extrema of curvature, and points with a large distance to the chords formed by pairs of previously identified neighboring dominant points. At each dominant point, a multi-dimensional feature vector is extracted, which includes a combination of coordinate features, delta features, and double-delta features.

Abstract: A communication system and device that enables free-hand drawn SMS (Short Messaging Service) messages to be transmitted and received from/to various user devices. A buffer device is inserted within a GSM compatible handset providing a buffer for both conventional SMS messages created by typing a message on the keypad of the handset and for free-hand drawn SMS messages created by drawing or writing the free-hand message on a data entry device. An optional OCR (Optical Character Recognition) facility can be provided in either the buffer device inserted within the handset or in a network server that receives the transmitted message and processes it for proper routing to the intended recipient.

Abstract: One or more techniques and/or systems are disclosed for compensating for affine distortions in handwriting recognition. Orientation estimation is performed on a handwriting sample to generate a set of likely characters for the sample. An estimated affine transform is determined for the sample by applying hidden Markov model (HMM) based minimax testing to the sample using the set of likely characters. The estimated affine transform is applied to the sample to compensate for the affine distortions of the sample, yielding an affine distortion compensated sample.

Abstract: Techniques for recognizing discrete multi-component symbolic input from a user can be applied to, for example, handwriting or speech. The techniques can include providing a database of model input sequences, where each model input sequence corresponds to a symbol to be recognized. Input functions, for example, discrete strokes, are obtained from a user and segmented into a sequence of discrete components. Hypothesis symbol sequences are obtained by comparing the discrete components to a database of symbols to be recognized and updating hypothesis symbol sequences based on the results of the comparison and hypothesis symbol sequence history from input previously acquired in time.

Abstract: One or more techniques and/or systems are disclosed for constructing a compact handwriting character classifier. A precision constrained Gaussian model (PCGM) based handwriting classifier is trained by estimating parameters for the PCGM under minimum classification error (MCE) criterion, such as by using a computer-based processor. The estimated parameters of the trained PCGM classifier are compressed using split vector quantization (VQ) (e.g., and in some embodiments, scalar quantization) to compact the handwriting recognizer in computer-based memory.

Abstract: A novel symbollogy derived from the lower-case cursive English alphabet (which is compatible with Latin alphabet derived languages), and a multi-step identification program designed to invoke the strengths of the XY Cartesian coordinate mapping system and a specific multi-step identification criteria designed to work in concert so as to allow absolute identification of each symbol. Each symbol is written onto an electronic tablet capable of identifying and distinguishing each individual symbol from a range of possible stroke patterns and then outputting or storing the symbol's assigned English alphabet counterpart. The combination of this symbollogy and recognition program allows high writing speed with the highest possible recognition potential.

Abstract: A method for determining the orientation of Chinese words is provided. The amount of dark pixels in each column of a Chinese word image is calculated. Then, a first point, a second point, and a third point are determined. The first point and the second point correspond to the columns with the largest and the second largest amount of dark pixels, respectively. The third point is located between the first point and the second point. The Chinese word is right-side up if the third point is located on the left side of the Chinese word. The Chinese word is upside down if the third point is located on the right side of the Chinese word.

Abstract: When a predetermined anomaly has occurred in a digital multifunctional machine, the fact of the anomaly occurring is notified to the service center and the computer at the guardhouse. The service person sent out from the service center is issued with an entrance permit from the entrance permit issuing device at the guardhouse. Then, the service person can pass through the passage gates in the building using the information recorded in the entrance permit and reach the place where the digital multifunctional machine is installed.

Abstract: A handwriting recognition device includes a main body having a side surface and an operation surface perpendicularly connecting to the side surface, and a first lens module and a second lens module arranged at opposite sides of the side surface. A first optical axis of the first lens module extends to perpendicularly cross a second optical axis of the second camera module outside the side surface. An overlapped area of a view angle of the first lens module and a view angle of the second lens module is defined as an input area. The first lens module is configured to capture a first picture of a handwriting tool in the input area. The second lens module is configured to capture a second picture of the handwriting tool in the input area. The handwriting recognition device calculates coordinates of the handwriting tool according to the first and the second pictures.

Abstract: Disclosed herein is a system for operating chirographic devices. The system may support a spatial chirographic sign reader, a spatial character recognition technique, a chirographic text character writer, a chirographic text character setter, a chirographic text character scanner, a spatial chirographic sign rendering technique, and a spatial chirographic styling sign marker. The system may include a central system unit having a real-time timer clock and bus connectors for chirographic input and output devices. Input device drivers may be adapted to collect spatial chirographic data and label samples with real-time data acquisition. Data may be transferred to chirographic applications of the system for character recognition, text setting, handwriting page scanning, sign styling, and image rendering to achieve specific chirographic effects.

Abstract: A handwritten data management system having an input device, and a handwritten data management apparatus having a screen to draw an image, wherein the input device has a sensor section to detect input device conditions, and sends the condition information to the management apparatus, wherein the management apparatus includes: a graphic data extracting section which extracts basic drawing data from trajectories of the input device on the screen; a break discrimination section which discriminates a break portion of the basic drawing data based on the condition information, and determines its break level by referring to a previously stored table; and a group data management section which groups plural basic drawing data, and registers the group data at a higher hierarchy level, and further sequentially groups the plural group data based on the break level, and registers a higher level group data at a higher hierarchy level.

Abstract: A system and methods of language identification of natural language text are presented. The system includes stored expected character counts and variances for a list of characters found in a natural language. Expected character counts and variances are stored for multiple languages to be considered during language identification. At run-time, one or more languages are identified for a text sample based on comparing actual and expected character counts. The present methods can be combined with upstream analyzing of Unicode ranges for characters in the text sample to limit the number of languages considered. Further, n-gram methods can be used in downstream processing to select the most probable language from among the languages identified by the present system and methods.

Abstract: A method for inputting character pairs in an electronic device having a user input device, a display for displaying characters input through the user input device, and a memory for storing characters input through the user input device, including storing a character input through the user input device in the memory and displaying the input character on the display; and determining if the input character is an opening character of a predefined character pair, and if so, automatically and without further user input, causing a corresponding closing character of the predefined character pair to be inserted in the memory and on the display, and locating an input pointer so that subsequently input characters will be inserted between the opening and closing characters in the memory and on the display.

Abstract: A input method selects a character from a plurality of characters of a logographic script, and identifies characters proximate the selected character. One or more candidate characters are then selected based on a composition input and the proximate characters.

Abstract: An information recognition system includes: a display section displaying an image on a display surface at a predetermined display resolution; an image combining section combining a character entry guide with the image, the character entry guide assisting handwritten input to the display surface; an information detecting section detecting handwritten input information at a detection resolution which is higher than the display resolution, the handwritten input information input to the display surface according to the character entry guide; and a character recognizing section performing character recognition based on the information detected at the detection resolution.

Abstract: A printer, scanner device and methods for using same are described herein. A printer device may include a dedicated input that, when actuated, generates and sends a request to a computer for known data or a predetermined print job, e.g., schedule information from a personal information management (PIM) application. A scanner device may include another dedicated input that, when actuated, automatically scans a document fed to the device by the user and sends the scanned image to IM (or other) software on a computer, bypassing the need to manipulate the scanned image using scanner software. The device may be used with printed metapaper, which includes a barcode or other indicia identifying the metapaper and corresponds to a stored template image of the metapaper. When the metapaper is rescanned, the scan can be compared to the stored template information to identify changes and synchronize the changes with the IM software.

Abstract: To provide a noise eliminating apparatus and the like that can eliminate an atypical shaped background noise. A character noise eliminating apparatus includes a character noise area detecting device for detecting a character noise area which is an area corresponding to a character noise from an image, a density conversion area layer determining device for setting a plurality of density conversion area layers inside and outside the character noise area, and a density converting device for setting a neighboring pixel group within the same density conversion area layer as the density conversion area layer to which a target pixel belongs as a reference area of the target pixel, with respect to pixels in the density conversion area layers, and generating a density converted image applying a local image enhancement.

Abstract: A method and system provides intelligent node-link diagram creation and editing, including an electronic display device having a surface on which a writing and/or drawing canvas is provided. An input device permits writing and/or drawing of electronic ink strokes, and a computing device is in operative association with the electronic display and the input device, and has stored therein for operation in connection with actions of the input device, a user interface (UI). The UI includes a graphical user interface (GUI) module, which controls input and display of the ink strokes applied to the canvas by the input device, and a recognition module which interprets the ink strokes by performance of structure recognition operations.

Abstract: According to one embodiment, a computing system includes a computing node coupled to a number of sensors. The sensors are operable to generate records from received information and transmit these records to the computing node. The computing node is operable to bind the plurality of records in a plurality of classifications using a multiple level classifier such that each classification has a differing level of specificity.

Abstract: In embodiments consistent with the subject matter of this disclosure, a user may input strokes as digital ink to a processing device. The processing device may partition the input strokes into multiple regions of strokes. A first recognizer and a second recognizer may score grammar objects included in regions and represented by chart entries. The scores may be converted to a converted score, which may have at least a near standard normal distribution. The processing device may present a recognition result based on highest converted scores according to a recurrence formula. The processing device may receive a correction hint with respect to misrecognized strokes and may add a penalty score with respect to chart entries representing grammar objects breaking the correction hint. Incremental recognition may be performed when a pause is detected during inputting of strokes.

Abstract: A method for classifying a handwritten input character is disclosed. Character models are used. Each character model is associated with an output character and defines a model specific segmentation scheme for that output character and an associated segment model. The model specific segmentation scheme defines a minimum length corresponding to a number of points in a stroke of the output character and a minimum length threshold. Using each of the character models, the input character is decomposed into segments and the segments are evaluated against the segment model of the respective character model to produce a score indicative of the conformity of the segments with the segment model. The character model that produced the highest score is selected and the input character is classified as the output character associated with the character model that produces the highest score.

Abstract: Methods, systems and user interfaces for providing feedback to a user based on recognition of character-based ink input are provided. A first feedback is provided to the user to indicate a character as which ink input by the user is recognized. The first feedback is displayed in proximity to the displayed input ink so that the user knows to which ink character the first feedback corresponds. A second feedback may optionally also be provided indicating a correctness of the recognized ink input, as compared to a predefined correct value such as a correct word game solution or answer, by displaying the input ink in one format to indicate that the recognized value is correct, and by displaying the input ink in a second format to indicate that the recognized value is incorrect.

Abstract: A medical device system and method for monitoring a patient include a monitoring device for storing data relating to the patient and a digital pen for digitizing and storing data handwritten by the patient. A control module is configured to aggregate data stored by the monitoring device and handwritten data stored by the digital pen.

Abstract: A method of classifying a character string formed from a known number of hand-written characters is disclosed. The method starts by determining character probabilities for each hand-written character in the character string. Each character probability represents a likelihood of the respective hand-written character being a respective one of a plurality of predetermined characters. Each predetermined character has a respective character type. Character templates having the known number of characters are next identified. Each character template has a respective predetermined probability and represents a respective combination of character types. Character sequence probabilities corresponding to each of the character templates having the known number of characters are next determined. The character sequence probabilities are a function of the predetermined probability of the respective character template and the character probabilities of the hand-written character in the character string.

Abstract: According to one aspect, the invention provides a system for validating an identity of a user to enable or prevent an occurrence of an event. In one embodiment, the system includes a first device including a wireless transmitter which is configured to transmit validation information, a second device including a wireless receiver, where the second device is configured to receive the validation information and further transmit the validation information; and a secure system in communication with the second device. According to one embodiment, the secure system includes a database. In a further embodiment, the secure system is configured to receive the validation information transmitted from the second device, and to transmit additional information to the second device following a receipt of the validation information to assist the second device in either enabling or preventing the occurrence of the event.