Character recognition by time-frequency analysis using writing pressure

With the development of information and communication technology, personal verification becomes more and more important. In the future ubiquitous society, the development of terminals handling personal information will require personal verification technology. The signature is one of the personal verification methods; however, the number of characters is limited in the case of the signature and therefore false signatures are easily used. Thus, personal identification from handwriting is difficult. This paper proposes a "haptic pen" that extracts the writing pressure, and shows a character recognition method based on time-frequency analyses. Although the figures of characters written by different writers are similar, the differences appear in the time-frequency domain. As a result, it is possible to use the proposed character recognition for personal identification more exactly. Experimental results show the viability of the proposed method.