We propose an on-line writer recognition method for Thai hased on velocity of harycenler of pewpoint movement. The harycenter is determined from the center point of script and two adjacent pen-point [wsitiuns with respect lo time in handwriting process. In this paper, the Fourier coefticients V I the velocity and trajectory of the barycenter are considered as the input antl output of PlR(finite impulse response) system. rcslicctively. In this case. the impulse response of the FIR system is interpreted as the feature of handwriting. The K-L expansion of the impulse response is used for writer recognition. Writer recognition experiments are performed on datahae cnnsistinp of 6.642 Thai scripts written by 81 writers. As the result. Type I(false rejection) and Type Il(fa1se acceptance) C R O~ rates were 1.50% and O.fjS%, respectively.

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This paper presents a robust coin recognition method with rotation invariance. The rotation invariance feature is represented by the absolute value of Fourier coefficients of polar image of coin on circles with different radii. The absolute value of Fourier coefficients is considered as the individual feature of the particular coin. Moreover, in this paper, the variations on surface of coin such as light reflection effect, are taken into account. Such variations effect can be reduced using the Fourier approximation of the coin image. Finally, coin can be recognized by the distance between the absolute value of Fourier coefficients obtained from the reference coin and the coin to be recognized. The coin recognition experiments are given to show the effectiveness of the proposed method.

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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%.