Motorola Corporation

Motorla, Inc.

John Lorne Seybold

Elton B Sherwin

Kannan Parthasarathy

Kenneth J Guzik

Ronjon Nag

Michael Mehrdad Hoghooghi

Liyang Zhou

Thomas Edward Buss

Farzad Ehsani

Coordinates from a digitizing tablet are processed in two modes. In a first mode (denoted the Cursor Mode for convenience) the digitizing tablet operates similar to the well know computer 'mouse' allowing the user to move the cursor around the display screen to select buttons and controls by mapping the coordinates to the display area of the monitor. In a second mode (denoted as the Input Mode for convenience), the digitizing tablet coordinates (especially generated by the motion of a pen) are mapped to an input area within a graphical interface of a computer program designed to accept handwritten input. Selection between the first mode and the second mode is made manually by switch input or automatically via analysis of the coordinates or by differentiating field sensing digitization from touch sensitive digitization.

Method and apparatus for multi-mode handwritten input and hand directed

A cellular telephone (100) has a receiver (506) and a transmitter (508) and a detachable battery (106) retrofitted for entering handwritten information and for providing power to the cellular telephone (100). The detachable battery (106) has a digitizer (552) for accepting the handwritten information, a recognition engine (560), coupled to the digitizer (552), for generating readable characters from the handwritten information. The detachable battery also has a memory (558), coupled to the recognition engine (560), for storing the readable characters and an output port (116) for transferring readable characters from the detachable battery (106).

Method for entering handwritten information in cellular telephones

An adaptive weighting handwriting recognition device and method compares information representing handwritten input with stored recognition data at least some of which has a weighting value associated therewith. The weighting values remains fixed during comparison of the handwritten input and stored recognition data and provide candidate recognition information, which can be further processed with user editing instructions to modify and correct the candidate recognition information. During user editing, the weighting values of the stored recognition data associated with the corrected candidate recognition information modified are varied to enhance the likelihood of correct future handwriting recognition.

Device and method for handwriting recognition with adaptive weighting of

The method and microprocessor of the present invention includes a step of calculating the angle changes, in the handwritten input. The method then selects potential segmentation points in the input whose angle change exceeds a predetermined threshold. The segmentation points are used to determine a sequence of straight line strokes that may be used by a recognizer for interpretation of the handwritten input.

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Palo Alto, CA, United States of America

John Lorne Seybold