Aggressive compression of the dynamics of handwriting and signature signals

The fields of biometrics and handwriting recognition can benefit from the presented aggressive compression techniques. A novel approach to compressing the on-line handwriting signal without losing the dynamic information (i.e., velocity) is presented; it provides the means of fitting almost any signature sample within the 57-byte limit of one of the free magnetic strips on conventional credit cards. The method starts with segmenting the on-line handwriting signal into portions which may be approximated by a set of features from which the velocity and position may be reconstructed. These features are then compressed further using a standard compression technique. A Huffman coding technique is used to bring the size of the average signature, including its dynamic information, below the 57-byte limit of credit card magnetic strips.. Normally, two of these strips are blank and may be used for storing the template of the owner´s signature for future verification