On-line writer dependent character recognition for Khmer based on FIR system characterizing handwriting motion

Abstract

We proposed an on-line writer dependent Khmer recognition method based on FIR system characterizing handwriting motion. The handwriting motion can be described by two features, barycenter trajectory and its velocity. The barycenter is determined from the center point of the script and the two adjacent pen-point positions with respect to time in handwriting process. Then the barycenter and its velocity are expanded into wavelet series to extract the time-frequency characteristics of handwriting motion. In this paper, the FIR(finite impulse response) system characterizing the handwriting motion is introduced. In this case, the wavelet coefficients of the velocity and trajectory of the barycenter are used as the input and output of the FIR system, respectively. The obtained impulse response of the FIR system is considered as the individual feature for a particular character. Finally, Khmer alphabets can be recognized by using the Euclidean distance between the impulse responses obtained from the reference alphabets and those of the alphabets to be recognized. Khmer character recognition experiments were performed on a database consisting of 4770 of numerals and alphabets written by 15 people. As the results, the average of the recognition rate was 97.05%.

On-line writer identification method based on FIR system characterizing pen-tip movement

“…In the works, [4]and [5], the time-frequency characteristics of pen-tip position in handwriting process were extracted. In the works, [6], [7] and [8], the handwriting feature was described by Fourier series approximation of handwriting process. However some fluctuation included in the handwriting feature could not be removed in the works, [6], [7] and [8].…”

FIR signature verification system characterizing dynamics of handwriting features

“…In this study, the wavelet coefficients of the dynamic handwriting features obtained in the preceding section are used as the input and output of the FIR system. The effectiveness of using the FIR system characterizing the handwriting feature for character recognition was reported in our work [25]. Figure 9 shows the FIR system in representing the time-frequency characteristics of handwriting features.…”

“…However, in several studies, a linear combination of several features of handwriting was used to verify signature: the suitable weight given to each feature in the linear combination is difficult to determine. Most papers have considered a fusion of independent features, but few papers [14][15][16] have considered the dynamic relation between the features. In this paper, the barycenter instead of the pen-point position is used to extract the stable handwriting feature.…”

“…In those studies, the individual features of a signature are extracted using the pen-point position, pen pressure, and pen inclination. Many techniques have been used to extract the feature of handwriting and verify the signature, such as DP (Dynamic Programming) matching [6][7][8][9][10][11], hidden Markov model [12,13], Fourier series [14][15][16], and support vector machine [17,18]. However, in several studies, a linear combination of several features of handwriting was used to verify signature: the suitable weight given to each feature in the linear combination is difficult to determine.…”

“…The details on how to determine the impulse response are reported in Thumwarin's work [15]. Figure 10 shows the impulse responses of the FIR system characterizing individual dynamics in the signing process, which are http://asp.eurasipjournals.com/content/2013/1/183 handwriting feature.…”