Abstract: A method may determine that an application with access to a media input resource has been launched by a user. A method may in response to determining that the application is launched, initiate a display of a settings user interface including a control for modifying a media input resource setting accessible via the operating system. A method may control transmission of a media output to the application based on the media input resource setting.

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: A method of searching a database containing documents with handwritten annotations stored in association with document content is disclosed. The method receives as inputs a handwritten annotation as a handwritten search input and a content element as a content search input. A search is then performed of the database for handwritten annotations in a document matching the handwritten search input and less than a given physical distance from document content equal to the content search input in the document.

Abstract: A method of decoding a coding pattern disposed on or in a substrate. The method comprises the steps of: (a) operatively positioning an optical reader relative to a surface of the substrate; (b) capturing an image of a portion of the coding pattern, the coding pattern comprising a plurality of square tags of length/identifying two-dimensional location coordinates; and (c) sampling and decoding x-coordinate data symbols within the imaged portion and y-coordinate data symbols within the imaged portion. The imaged portion has a predetermined diameter and is guaranteed to contain sufficient data symbols from each of the Reed-Solomon codes so that symbol errors are correctable in each of the codes during the decoding.

Abstract: A system for modifying a classification scheme for classifying hand-written characters. The system includes a memory storing the classification scheme containing a plurality of user dependent allographs, each allograph representing a respective style of a respective letter; and a processor configured for: receiving data representing a handwritten character; selecting an allograph representing the handwritten character; modifying the allograph in accordance with the selection; and storing a modified classification scheme which includes the modified allograph.

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, and a 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 ? ? 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: A handwritten character recognition system is disclosed. The system has an input device for receiving handwritten strokes, and a processor for classifying the handwritten strokes as an output character. The processor does so by calculating a degree of membership of the handwritten strokes to each of a plurality of character models. The character model that produces the highest degree of membership is selected and the handwritten strokes ate classified as the output character associated with the character model that produces the highest degree of membership.

Abstract: A substrate having a coding pattern disposed thereon or therein. The coding pattern comprises a tiling of contiguous grid cells, each grid cell being demarcated by t target elements and having t-fold rotational symmetry, each grid cell containing nt registration symbols, each registration symbol being encoded by a set of macrodots; and a tiling of contiguous tags, each tag consisting of an array of c grid cells, each tag containing a plurality of data symbols. There are ct possible registrations between a physical layout of the coding pattern and a logical layout of the coding pattern and any contiguous tag-shaped array of c grid cells contains cnt registration symbols. The registration symbols, taken in a defined sequence relative to the physical layout of the tag-shaped array, form a registration codeword of length r. There are v distinct registration codewords, each corresponding to a distinct one of the ct possible registrations.

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: A character classification system is disclosed. The character classification system has an input device for receiving a handwritten input character, and a processor. The processor is configured to, for each character model, each character model being associated with an output character and defining a model specific segmentation scheme for that output character and an associated segment model, the model specific segmentation scheme defining a minimum length corresponding to a number of points in a stroke of the output character: (i) decompose the handwritten input character into one or more segments in accordance with the model specific segmentation scheme of the respective character model; and (ii) evaluate the one or more segments against the segment model of the respective character model to produce a score indicative of the conformity of the one or more segments with the segment model.

Abstract: A substrate having a coding pattern disposed therein or thereon. The coding pattern comprises: a tiling of contiguous grid cells, each grid cell being demarcated by t target elements and having t-fold rotational symmetry, each grid cell containing nt control symbols, each control symbol being encoded by a set of macrodots; and a tiling of contiguous tags, each tag consisting of an array of c grid cells, each tag containing a plurality of data symbols, each data symbol being encoded by a set of macrodots. Any contiguous tag-shaped array of c grid cells contains cnt control symbols, which encode r1 registration symbols and r2 second symbols. The r1 registration symbols, taken in a defined sequence relative to a physical layout of the tag-shaped array, form a registration codeword of length r1. The r2 second symbols form one or more second codewords.

Abstract: A method of decoding a coding pattern disposed on or in a substrate.

Abstract: A method of searching a digital ink database is disclosed. The digital ink database is associated with a specific author. The method starts by receiving a computer text query from an input device. The computer text query is then mapped to a set of feature vectors using a handwriting model of that specific author. As a result, the set of feature vectors approximates features that would have been extracted had that specific author written the computer query text by hand. Finally, the set of feature vectors is used to search the digital ink database.

Abstract: A system and method for ink database searching using handwriting feature synthesis is disclosed which allows a digital ink database to be searched using a text-based query. Using a writer-specific handwriting model derived from a handwriting recognition system or suitable training procedure, a text query is converted into feature vectors that are similar to the feature vectors that would have been extracted had the author of the digital ink database written the text query by hand. The feature vectors are then used to search the database.

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, and a 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 ? ? 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: 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. 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: 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: 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: A system for modifying a classification scheme for classifying hand-written characters. The system includes a memory storing the classification scheme containing a plurality of user dependent allographs, each allograph representing a respective style of a respective letter; and a processor configured for: receiving data representing a handwritten character; selecting an allograph representing the handwritten character; modifying the allograph in accordance with the selection; and storing a modified classification scheme which includes the modified allograph.

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.