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[Keyword] Writer recognition(2hit)

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  • On-Line Writer Recognition for Thai Numeral

    Pitak THUMWARIN  Takenobu MATSUURA  

     
    PAPER-Source Coding/Image Processing

      Vol:
    E86-A No:10
      Page(s):
    2535-2541

    In this paper, we propose an on-line writer recognition method for Thai numeral. A handwriting process is characterized by a change of numeral's shape, which is represented by two features, a displacement of pen-point position and an area of triangle determined from the two adjacent points of pen-point position and the origin. First, the above two features are expanded into Fourier series. Secondly, in order to describe feature of handwriting, FIR (Finite impulse response) system having the above Fourier coefficients as input and output of the system is introduced. The impulse response of the FIR system is used as the feature of handwriting. Furthermore, K-L expansion of the obtained impulse response is used to recognize writer. Writer recognition experiments are performed by using 3,770 data collected by 54 Thai writers for one year. The average of Type I (false rejection) error rate and Type II (false acceptance) error rate were 2.16% and 1.12%, respectively.

  • A Text-Independent Off-Line Writer Identification Method for Japanese and Korean Sentences

    Mitsu YOSHIMURA  Isao YOSHIMURA  Hyun Bin KIM  

     
    PAPER

      Vol:
    E76-D No:4
      Page(s):
    454-461

    This paper proposes an off-line text-independent writer identification method applicable to Japanese and Korean sentences. It is assumed that the writer of a writing in question exists in a certain group of people and that reference writings written by each person in the group can be used for identification. In the proposed method, relative frequencies of some model patterns are counted on the binary pattern of each writing and are used as the feature to measure the distance between two writings. Based on a modified Mahalanobis' distance for this feature, the person whose reference writing is nearest to the writing in question is judged as the writer. The effectiveness of the proposed method is examined through an experiment using Japanese and Korean writings. Error rates in the experiment were different depending on conditions such as volume of reference writings, dimension of adopted features, and number of people to be identified. In some cases, error rates as low as 0% were observed. Error rates tend to be lower in Korean writings probably because Hangul is composed of a smaller number of letters compared to Kanji and Hiragana in Japanese writing.