Recognizing handwriting input using rotatable support lines

摘要

Software, firmware, and systems are described for identifying characters in a handwritten input received from a user on an input device, irrespective of an angle that the input is received at. In one implementation, the system establishes an anchor point and distances from the anchor point to reference support lines. A set of candidate characters is identified based on received handwritten input. The system estimates support lines for each of the candidate characters. The system ranks the candidate characters based on a total deviation measurement from the expectation for each candidate, where the expectation in part is based on the established distance from the established anchor point to reference support lines, and identifies a best-ranked candidate based at least in part on a smallest total deviation measurement.

主权项

1. A method for identifying characters in a handwritten input on a touch-sensitive device, the method comprising:
establishing an anchor point on the touch-sensitive device; establishing distances from the anchor point to one or more reference support lines; receiving a handwritten user input via the touch-sensitive device; identifying a set of candidate characters based on the handwritten user input; estimating support lines for each of the candidate characters; associating temporary reference support lines for each candidate character based on: an angle of the estimated support lines for the candidate character and the established anchor point, and the established distances from the anchor point to the one or more reference support lines; for each candidate character,
measuring a deviation between the estimated support lines and temporary reference support lines to determine a scale and position deviation from an expectation for each candidate character, andcombining the measured deviation with candidate expectation deviation measurements for properties other than scale and position; ranking each candidate character based on a total deviation measurement for each candidate character; and, identifying a best-ranked candidate character based at least in part on a smallest total deviation measurement.