Team Number: 025
School Name: Eldorado High School, Manzano High School
Area of Science: Miscellaneous
Project Title: Adaptive Handwriting Recognition and Identification
Handwriting recognition and comparison, though previously and frequently
implemented, has rarely supported input from multiple users without
distinct prior identification of the active user providing input.
Adaptive algorithms can be incorporated with existing methods of
handwriting identification in order to compare arbitrary samples with
pre-recorded database entries of font file-like handwriting samples which
have been identified with their writers. Such a program would allow for
reliable computational comparison usable in environments such as court
situations and banking.
Our project's goal is to implement such an algorithm in order to match
handwriting input within a database of stored handwriting samples.
We intend to model analog handwriting analysis techniques, using a time
parameter to identify how letters are written as a means of comparison in
addition to shape comparison with individual letters. The general methods
used by handwriting analysts to identify who wrote a letter based on the
motions involved in its writing would first be used to identify which
database file to use, and then the letters would be identified by shape
Progress to Date:
We have written C++ objects to manage bitmaps (with member functions to
binarize and thin letter images to single pixels so that they may be
better identified), database files (capable of storing user identification
data and standardized letter image positioning, in order to arbitrary
determine the location and size of individual letters), and letters in our
program and have begun to delve into the important steps of implementing
the input and identification routines. We may require a touch input
device in order to continue with programming our projects, since a time
parameter is virtually impossible to implement without realitme input.
Considering our limited progres thus far and the magnitude of the steps
ahead, it may be unreasonable for us to expect project completion by the
deadline. However, assuming we do complete the project, we expect to be
able to identify several fairly distinct handwriting samples from one
another with ease.