A Compression Scheme for Handwritten Patterns Based on Curve Fitting

We present here an idea of compression of user fed data from a touch screen input interface for storage and transmission over relatively lower bandwidth. The input is taken in the form of hand-written text, graphics, symbols or patterns and recorded as strokes in order of their temporal occurrence. The patterns are segmented into primitive forms each of which is then modeled with third order B-Spline Curves. The number of control points driving the Spline Curve is determined beforehand by recognizing the dominant points in the pattern. The significant reduction of redundancy in data can be exploited in wide application base including low-cost handheld device communication. This algorithm hence proposes a language independent tool for recording the handwriting of user in its original essence. Results obtained from preliminary testing on MATLAB and Android platform show significant improvement in compression ratio over the traditional storage and compression schemes.