Abstract: A system and method for assisting with analysis and recognition of ink is described. Analysis hints may be associated with a field. The field may receive electronic ink. Based on the identity of the field and the analysis hint associated with it, at least one of analysis and recognition of ink may be assisted.

Abstract: A pen-enabled computing arrangement includes a handwriting capture interface and at least one processing element, such as in the form of a computing system and a digital pen that embodies a writing stylus. The handwriting capture interface can capture an electronic handwriting input. The processing element can sense an identifier associated with an object, and associate electronic handwriting input with the object. The processing element can then process the electronic handwriting input based upon the associated object. Printed paper with which the arrangement can operate to effectuate capturing and processing data may also be provided. Further, triggered verification of the sensed identifier may be provided when the identifier is sensed based upon initial electronic handwriting input corresponding to the identifier and the sensed identifier is unknown and/or improper.

Abstract: An improved system and method for providing context information of executable code to an input method is provided. Advanced text input methods may be made aware of the type of text expected to be received as input so that input methods may achieve a higher accuracy in recognition of text input. Generic interfaces provide a framework for supporting application authoring platforms to allow application developers to easily specify context information to the system and have it reliably forwarded to the correct input methods. Additionally, a context tagging tool may associate specific text input fields of an existing application with an input scope without modifying the application itself. The context tagging tool may create a manifest that contains tags associating the specific text input fields with an input scope. Any advanced input methods use by the application may be updated with instructions for accessing the context information stored in the manifest.

Abstract: The invention provides a method/system for estimating the orientation of a segment of digital ink using pen orientation information. In one form, the invention is a method of estimating the orientation of a segment of digital ink, the method including the steps of: measuring the azimuth of the pen at a sampling rate during writer generation of the segment of digital ink; and estimating the orientation of the segment of digital ink using the measured azimuth of the pen at sampled points.

Abstract: The invention provides a method/system for estimating the orientation of a segment of digital ink using pen orientation information. In one form, the invention is a method of estimating the orientation of a segment of digital ink, the method including the steps of: measuring the azimuth of the pen at a sampling rate during writer generation of the segment of digital ink; and estimating the orientation of the segment of digital ink using the measured azimuth of the pen at sampled points.

Abstract: A system is presented for scanning entire books or document all at once using an adaptive process where the book or document has known fonts and unknown fonts. The known fonts are processed through a verification system where sure words and error words are determined. Both the sure words and error words are sent to OCR training where they are re-OCR'ed and repeatedly verified until they meet a predetermined quality criteria. Characters or words not meeting the predetermined quality criteria receive additional OCR training until all the characters and words pass the predetermined quality criteria. Unknown fonts are scanned and clustered together by shape. Outliers in the shapes are manually keyed-in. Those symbols that are manually classified go to OCR training and then to the known type optimization process.

Abstract: Various technologies and techniques are disclosed that improve cursive handwriting recognition. Cursive handwriting input is received from a user. The system performs a hierarchical prototype search as part of a recognition operation. A same space search is performed against a mixed database that has both print and cursive samples. A same space search is also performed against a cursive database that has only cursive samples. The results of these two same space searches are merged into a combined alternate list. The combined alternate list is then used as a constraint for the dynamic time warp searches that are performed against the mixed and cursive databases, respectively. The results of the dynamic time warp searches are also merged into a final combined alternate list, and the combined alternate list is used to make a recognition decision regarding the user's handwritten input.

Abstract: Various computer-implemented methods are provided. One method for signature recognition includes identifying a vertical element of a signature and determining a tilt angle of the vertical element. Tilt angle is defined by a line that is approximately parallel to the vertical element. In addition, the method includes determining a tilt factor. Tilt factor is defined as a horizontal offset between the tilt angle and a reference tilt as a function of distance from a signature baseline. The method further includes altering the signature using the tilt factor and comparing the altered signature to known signature(s) to determine if the altered signature matches one of the known signature(s). Another method includes altering the signature using a predetermined tilt factor and comparing the altered signature to known signature(s). If the altered signature does not match one of the known signature(s), these steps may be repeated with different predetermined tilt factors.

Abstract: An application programming interface instantiates an ink analyzer object that receives document data for a document containing electronic ink content from a software application hosting the document and running on a first processing thread. The ink analyzer object then employs the first thread to make a copy of the document data, provides the copy of the document data to an electronic ink analysis process, and returns control of the first processing thread to the analysis process. After the analysis process has analyzed the electronic ink, the ink analyzer object reconciles the results of the analysis process with current document data for the document.

Abstract: In a method and system to extract data from handwritten information when the information is captured as sequences of strokes, vectors, or marks, temporal data is stored within the color or gray-scale encoding of pixel values within a bitmapped image. A bitmapped image is used to create a derived image suitable for data extraction and a method of analyzing the image, including the encoded temporal data, to yield an adjusted image that better reflects the intent of the person who created the handwriting. While the primary application of the invention is in processing handwritten responses to assessment items, the system and method can be advantageously used to extract data from or to improve the presentation of information from an electronic representation of temporal human marks in many applications. Additionally, the system and method can be advantageously used to store and process other types of data within a bitmapped image.

Abstract: A word spotting system includes a semi-continuous hidden Markov model configured to model a handwritten word of interest. A writing segments extractor is configured to extract writing segments generally comprising images of handwritten character strings from a received document image. A word model adaptation processor is configured to adjust a shared pool of Gaussians of the semi-continuous hidden Markov model respective to the extracted writing segments. A modeler is configured to model extracted writing segments using the semi-continuous hidden Markov model with the adjusted shared pool of Gaussians to identify whether each modeled writing segment matches the handwritten word of interest.

Abstract: A method, system, and computer-readable medium containing computer-executable instructions are provided, for randomly relocating text character images of a scanned-in Asian character document to produce a shuffled image, wherein the meaning of text in the shuffled image is not understandable although individual characters forming the text in the shuffled image are recognizable. In one embodiment, the method includes generally four steps: (1) dividing an Asian character document image into a text image portion and a non-text image portion; (2) structuring the text image portion into a multiple resolution-level pyramid; (3) extracting shuffleable character images by analyzing the multiple-resolution-level pyramid; and (4) shuffling some or all of the extracted shuffleable character images to create a shuffled image. The shuffled (e.g., encoded) image can be reshuffled (e.g.

Abstract: A method for recognition of a handwritten pattern comprises selecting core points among a sequence of detected points of the handwritten pattern. The core points are selected for use in segmenting and recognizing the handwritten pattern. The method may further comprise identifying potential diacritics in the sequence of points of the handwritten pattern, determining features of each core point, assigning at least one feature associated with identified potential diacritics to each core point of a subset of core points, and comparing the handwritten pattern to templates.

Abstract: A system is provided having a database storing annotation digital ink representing handwritten annotations on a printed document and a processor configured to segment the annotation digital ink into lines by obtaining a stroke sequence comprised of a sequence of strokes, removing small strokes less than a threshold length, segmenting the strokes into a sequence of substrokes by computing a relative angle for each line segment connecting successive stroke data points and segmenting the stroke into substrokes if the difference between successive relative angles is greater than a preset threshold, and identifying the substrokes at line breaks, thereby facilitating line extraction, by computing N-neighbourhood centroids, computing angular differences between N-neighbouring substrokes, or groups of substrokes and computing local maxima of the angular differences in the sequence of substrokes.

Abstract: Systems and methods are disclosed that facilitate normalizing and beautifying digitally generated handwriting, such as can be generated on a tablet PC or via scanning a handwritten document. A classifier can identify extrema in the digital handwriting and label such extrema according to predefined categories (e.g., bottom, baseline, midline, top, other, . . . ). Multi-linear regression, polynomial regression, etc., can be performed to align labeled extrema to respective and corresponding desired points as indicated by the labels. Additionally, displacement techniques can be applied to the regressed handwriting to optimize legibility for reading by a human viewer and/or for character recognition by a handwriting recognition application. The displacement techniques can comprise a “rubber sheet” displacement algorithm in conjunction with a “rubber rod” displacement algorithm, which can collectively preserve spatial features of the handwriting during warping thereof.

Abstract: Methods and systems for facilitating the selection of alternates for hand written word. Rules select words user based on operating modes and cursor positions and sequential orderings. User interfaces can also be used to select words and to provide alternates for the selected words having alternates. Words that the recognizer believes correct to a high actual or relative probability may be skipped over in automatic processes, and the display of words that the recognizer is less confident are correct can be modified. The user can adjust such sensitivity settings for determining the probability of correctness.

Abstract: A digital signature method based on identification information of one or more group members who belong to a group includes: a) a group parameter generating operation generating group public key information and group secret key information corresponding to the group; b) a member registering operation generating member secret key information using identification information of the group members who belong to the group and an identification information digest value obtained by applying a predetermined hash function to the identification information, and transmitting the member secret key information to the group members; c) a digital signing operation generating a digital signature by applying a predetermined signature algorithm to the identification information and the identification information digest value, and transmitting the generated digital signature and a message; and d) an authentication operation verifying a validity of the digital signature by applying a predetermined authentication algorithm to the

Abstract: Computer-readable media having computer-executable instructions and apparatuses detect a table in a handwritten document. Line segments are derived from drawing strokes so that a bounding frame of a candidate table is obtained. An associated table structure is consequently recognized from the bounding frame, lines segments within the bounding frame, and their intersection points. A classifier that reflects at least one table characteristic is determined, and the candidate table is consequently validated or rejected.

Abstract: Handwriting recognition is performed by sensing a trace signal, where the trace represents a handwritten intended symbol. A digital representation of the trace signal is then stored and compared with a plurality of candidate symbols. Depending on the outcome of the comparison, a best candidate symbol among the candidate symbols is recognized and displayed, or the digital representation of the trace signal is displayed.

Abstract: A computer based method of biometric analysis which compares a first vector from a first biometric sample with a second vector from a second biometric sample. The vectors have at least one biometric feature. A method which compares two biometric samples. The samples form at least one cluster of at least one vector based on feature similarities between the samples. An apparatus incorporating a means for performing the method taught herein. A computer-readable medium and a propagated computer data signal transmitted via a propagation medium, with instructions which when executed by a processor, carry out the method of the present invention. A method of handwriting analysis which calculates a first metric from a first vector having at least one feature from a sample, calculates a second metric from a second vector having at least one feature from a second sample, and calculates the distance in two-dimensional feature space between metrics.

Abstract: A spatial motion recognition system capable of recognizing motions in three-dimensional space as handwritings on a two-dimensional plane is provided. The system recognizes motions of a system body occurring in space based on position change information of the system body that is detected in a motion detection unit, displays the recognized motion information on a screen, or transmits to an external device the recognized motion information through a transmission/reception unit or a control signal corresponding to the motion information. A control unit produces a virtual handwriting plane having the shortest distances with respect to respective positions in predetermined time intervals based on three-dimensional track information obtained through tracking, and projects the respective positions in the predetermined time intervals onto the virtual handwriting plane to recover the motions in space.

Abstract: A method for recognition of a handwritten pattern comprises selecting core points among a sequence of detected points of the handwritten pattern. The core points are selected for use in segmenting and recognizing the handwritten pattern. The method further comprises determining features of each core point, and comparing the handwritten pattern to templates. The comparing comprises stepwise analyzing the core points in sequence by matching the features of sequences of core points that either start with the first core point or the last core point of a previous sequence to said templates and calculating a distance value, and assigning a cumulative distance value to the last core point in the matched sequence of core points, whereby a smallest cumulative distance value is assigned to the last core point and corresponds to a sequence of matched templates which represent a possible recognition result of the handwritten pattern.

Abstract: Systems, methods, and computer-readable media process and distinguish user input device gestures, such as gestures input via a pen in a pen-based computing system, e.g., to quickly and reliably distinguish between electronic ink entry, single taps, double taps, press-and-hold actions, dragging operations, and the like. Systems, methods, and computer-readable media also are provided for dynamically calibrating a computer system, e.g., calibrating a displayed input panel view based on input data recognized and received by a digitizer. Such systems and methods may operate without entering a dedicated or special calibration application, program, or routine.

Abstract: A method and system utilizing both (x, y) coordinate (“spatial”) stroke data and associated pressure information for improved handwriting recognition. The method and system can also be applied to all types of handwriting-based data entry applications and also to user authentication. The digitizer pad used in the computer system gives both spatial information and associated pressure data when a stroke is being drawn thereon, e.g., by a stylus. Pressure information can be used to differentiate between different character sets, e.g., upper case and lower case characters for certain alphabetic characters. The spatial stroke data then identifies the particular character. The pressure information can also be used to adjust any display attribute, such as character font size, font selection, color, italic, bold, underline, shadow, language, etc. The associated pressure information can also be used for recognizing a signature. In this case, a user is allowed to sign a name on the digitizer pad.

Abstract: A method and system for cleaning handwriting for redisplay of the handwriting or for improved recognition accuracy is provided. The cleanup system receives handwriting that has been digitized. The cleanup system then analyzes the handwriting to identify strokes that satisfy a cleanup criterion. When a stroke has been identified as satisfying some cleanup criteria, the cleanup system cleans up the handwriting based on the detected criteria. In this way, the cleanup system generates handwriting that may have a more visually pleasing appearance to the reader.

Abstract: A method begins by receiving an image of a handwritten item. The method performs a word segmentation process on the image to produce a sub-image and extracts a set of feature vectors from the sub-image. Then, the method performs an asymmetric approach that computes a first log-likelihood score of the feature vectors using a word model having a first structure (such as one comprising a Hidden Markov Model (HMM)) and also computes a second log-likelihood score of the feature vectors using a background model having a second structure (such as one comprising a Gaussian Mixture Model (GMM)). The method computes a final score for the sub-image by subtracting the second log-likelihood score from the first log-likelihood score. The final score is then compared against a predetermined standard to produce a word identification result and the word identification result is output.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing part of a multi-path framework is described. The part of the multi-path framework includes a subscript/superscript analysis and character determination component that is designed to identify subscript and superscript elements. A method for analyzing a handwritten mathematical expression includes receiving a symbols corresponding to handwritten mathematical expression input strokes, identifying subscript and/or superscript structures, and determining a character for each symbol of the set. A graph of vertexes and edges may be created based upon the set of symbols and the graph may be searched to determine optimized candidates.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing a part of a multi-path framework is described. The part of the multi-path framework includes a symbol grouping and recognition component that is designed to group input strokes that correspond to a handwritten mathematical expression into a symbol and to recognize the symbol based upon information associated with the grouped input strokes. A method for grouping and recognizing symbols of a handwritten mathematical expression includes receiving a plurality of input strokes corresponding to a handwritten mathematical expression, grouping the plurality of input strokes into symbols, recognizing the symbols based upon information, such as shape and time series information, associated with the grouped input strokes. Intra-group and inter-group information associated with the plurality of input strokes may be utilized to group the input strokes.

Abstract: A mechanism for recognizing and inputting handwritten mathematical expressions into a computer by providing a multi-path framework is described. The framework may include symbol grouping and recognition, tabular structure analysis, subordinate sub-expression analysis, subscript/superscript analysis and character determination, and semantic structure analysis components. A method for recognizing a handwritten mathematical expression includes receiving a plurality of input strokes corresponding to a handwritten mathematical expression and providing a candidate list of recognized candidate expressions based upon the input strokes. Input strokes are grouped into symbols, tabular structures are determined, dominant symbol candidates and subordinate symbols are determined, and subscript and superscript structures are determined.

Abstract: A possible portion providing method involving receiving a pattern provided using a movable member, the pattern corresponding to a traveling path of the movable member, and the provided pattern corresponding to a portion of an intended sequence, determining at least one possible sequence which includes the received pattern, and displaying a remaining portion of the at least one possible sequence using a predefined font set for a plurality of components, the predefined font set including a record of a pattern corresponding to the traveling path of the movable member or another movable member for each of the plurality of components.

Abstract: An output mechanism of a character recognition device includes a category classifier for classifying image data of characters to be recognized for each category recognized in character recognition processing, a clustering processor for determining feature values related to shapes of characters included in the image data in each category classified by the category classifier, and for classifying the image data into one or more clusters based on the feature values, and a screen creator for creating a confirmation screen for displaying the image data for each cluster classified by the clustering processor.

Abstract: Methods and systems are provided for analyzing and assessing documents using a writing profile for documents, such as a payment instrument. A method may include providing a document to a computer system. In some embodiments, the method may further include obtaining information on writing in an information field of the document. In certain embodiments, the obtained written information in the information field and written information in at least one other information field may be compared to at least one writing profile representation. The writing profile representation may be obtained from at least one other document. In one embodiment, at least one of the writing profile representations may include written information from the information field and written information from at least one of the other information fields obtained from at least one of the other documents. In some embodiments, the comparisons may be used to verify the obtained written information.

Abstract: As a user writes using a handheld writing device, such as an electronic pen or stylus, handwriting input is received and initially displayed as digital ink. The display of the digital ink is converted to recognized text inline with additional digital ink as the user continues to write. A user may edit a word of recognized text inline with other text by selecting the word. An enlarged version of the word is displayed in a character correction user interface that allows a user to make corrections on an individual character basis and also provides other correction options for the word.

Abstract: Described is a computer-implemented system and method that detects and differentiates scratch-out gestures from other electronic ink, e.g., entered via a pen. The system and method compare boundary-based criteria to differentiate, which eliminates the need to have a specially-shaped scratch-out pattern, instead allowing a wide variety of scratch-out styles to be detected. Criteria includes boundary-based evaluations such as whether the potential scratch-out gesture intersects previously recognized words or characters, whether the scratch-out gesture has a width that is at least a threshold percentage of the width of a word or character bounding box, whether the electronic ink extends beyond the midpoint of the bounding box, and whether at least some portion of the scratch-out gesture is above a baseline of the word or character. Scratch-out gestures entered in freeform input writing areas and boxed input writing areas are supported.

Abstract: A method and apparatus for generating a template for use in handwriting recognition are provided. In the method and apparatus text is obtained, character strings in the text are identified, each character string being formed from a sequence of one or more characters and each character having a respective type, a sequence of character types is determined for each character string and a template is defined for each character type sequence.

Abstract: A computer-implemented system for obtaining ink annotations from paper comprises a comparator that compares an initial electronic version of a document with an electronic image of an annotated version of the document to identify a handwritten annotation. The system also includes an annotation lifter that extracts the handwritten annotation from the electronic image and converts the handwritten annotation into a computer-usable form. Methods for using the system are also provided.

Abstract: A system creates an electronic version of a document from page-images of the document, wherein the electronic version replicates both the logical content and the physical appearance of the original document. During operation, the system receives the page-images for the document. Next, the system extracts character images from the page-images, and generates a synthetic font for the document from the extracted character images. Finally, the system constructs the electronic version of the document by, using the synthetic font to represent text regions of the document, and by using image-segments extracted from the pages-images to represent non-text regions of the document.

Abstract: In a computing device, a method and system for searching for matching ink words or phrases, by comparing a given search term of at least one word (and possibly alternates) with the words in a document, including recognized ink words and any possible alternates for those recognized words as returned by a recognizer. Various matching tests are possible because of the use of alternates, which also may have corresponding probability rankings that may influence the search. Searching may occur in actively edited ink documents, or the recognition results may be saved as saved search file data that can be searched independent of recognition.

Abstract: A drawing assistance system enhances a sketch drawn by a user in an electrical document on a computer system by collecting stroke data from one or more strokes of a sketch as a user draws the sketch. The stroke data includes time-based information and features of each stroke. The strokes are handled based on the time-based information, and analysed based on the strokes handled based on the time-based information. The sketch is enhanced based on results of the analysis.

Abstract: A handwritten information management system, which includes a paper sheet document generation section that generates a paper sheet document in which plurality pieces of coded information including coordinate information indicating a position on a paper sheet and document identification information of the paper sheet document formed on the paper sheet are recorded; a paper sheet document registration section that registers the generated paper sheet document and an electronic document corresponding to the paper sheet document correlated with the document identification information; a handwritten information detection section that detects handwritten information handwriting on the generated paper sheet document; a handwritten information registration section that registers handwritten information identification information to identify the handwritten information correlated with the detected handwritten information; and an identification information management section that manages the document identification info

Abstract: The present invention provides a method of modifying a classification scheme for classifying hand-written characters to thereby make the classification scheme user dependent. The classification scheme includes a number of allographs, each allograph representing a respective style of a respective letter. The method includes obtaining at least one hand-written character, and then selecting an allograph representing the character. One or more of the allographs are then modified in accordance with the selection, to thereby reflect the fact that the allograph corresponds to a style of letter used by the user.

Abstract: A method of reconciling a first data structure with a second data structure that is a subsequently modified version of the first data structure. Initially, each node in the first data structure for which a change has been made to a corresponding node in the second data structure is accessed. For each accessed node, a determination is made as to whether the change made to the corresponding node in the second data structure creates a collision with the first data structure. If the change made to the corresponding node in the second data structure does not create a collision with the first data structure, then the change is made to the accessed node in the first data structure.

Abstract: Systems and methods are provided for correcting digital pen strokes written on a paper form using a digital pen. In one embodiment, a stroke collection file includes sets of coordinates corresponding to respective pen strokes written on the paper form including a mistake stroke that a user of the pen desires to correct and a removal stroke written through the mistake stroke using the digital pen. In one embodiment, the removal stroke includes a horizontal zigzag pattern having at least one horizontal extend further to the left and further to the right of the mistake stroke. In one embodiment, coordinates corresponding to the mistake stroke and the removal stroke are deleted from the stroke collection file. The stroke collection file may also include coordinates for a third pen stroke intended to replace the mistake stroke. One embodiment includes rendering an image of the paper form and the third pen stroke.

Abstract: The present invention employs the notion of a Chinese writing brush in moving a geometric figure to produce a style of calligraphy, where the area of the geometric figure is large or small, then the strokes of a character are thick or thin. Hence the purpose is that the variance of the strokes of a character can be achieved using the present invention. The present invention only decides a moving path for the strokes of a character and the size of a geometric figure at starting points and end points, and then moves the geometric figure along the moving path, where the area the geometric figure passes is the style of calligraphy.

Abstract: A method and system utilizing both (x, y) coordinate (“spatial”) stroke data and associated pressure information for improved handwriting recognition. The method and system can also be applied to all types of handwriting-based data entry applications and also to user authentication. The digitizer pad used in the computer system gives both spatial information and associated pressure data when a stroke is being drawn thereon, e.g., by a stylus. Pressure information can be used to differentiate between different character sets, e.g., upper case and lower case characters for certain alphabetic characters. The spatial stroke data then identifies the particular character. The pressure information can also be used to adjust any display attribute, such as character font size, font selection, color, italic, bold, underline, shadow, language, etc. The associated pressure information can also be used for recognizing a signature. In this case, a user is allowed to sign a name on the digitizer pad.

Abstract: Input is received from at least two different input sources. Information from these sources are combined together to provide a result. In a particular example, input from one source corresponds to potential recognition candidates, and input from another source corresponds to other potential candidates. These candidates are combined together to select a result.

Abstract: Systems and methods are provided for recognizing handwritten characters drawn on a paper form using a digital pen that records stroke coordinates corresponding to respective pen strokes. In one embodiment, a field on the paper form is assigned a lexical inference level. For example, the field may be assigned a word level, a word prefix level, and/or a word stem level. The assigned lexical inference level is used to recognize one or more stroke coordinates corresponding to pen strokes written in the field. Recognized characters are then used to create or modify an inference lexicon used to perform handwriting recognition for the entire field. In one embodiment, the inference lexicon is used for handwriting recognition in the same field on subsequently processed forms.

Abstract: A system and/or method that provides a virtual alpha-numeric keyboard based at least in part upon a user real-time input entry within a portable computing device. An input component receives an input providing a recognition component to determine and/or infer possible input entries (e.g., virtual keys). Once possible input entries are determined and/or inferred, a rendering component concurrently displays the virtual keys during the input entry.

Abstract: A machine-readable storage medium storing executable code is configured to cause a machine to randomly alter a shape of a character. A method for creating a dynamic handwriting font includes: providing a first shaped character; providing a predetermined frequency distribution; and randomly altering a shape of the first shaped character according at least partially to the frequency distribution.

Abstract: A system/method is presented for scanning entire books or document all at once using an adaptive process where the book or document has known fonts and unknown fonts. The known fonts are processed through a verification system where sure words and error words are determined. Both the sure words and error words are sent to OCR training where they are re-OCR'ed and repeatedly verified until they meet a predetermined quality criteria. Characters or word not meeting the predetermined quality criteria receive additional OCR training until all the characters and words pass the predetermined quality criteria. Unknown fonts are scanned and clustered together by shape. Outliers in the shapes are manually key-in. Those symbols that are manually classified go to OCR training and then to the known type optimization process.