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Online Handwritten Digit Recognition by Smith-Waterman Alignment

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2011, 16(9), pp.27-34
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

문원호 1 최연석 1 Lee Sang-Geol 1 CHA,EUI-YOUNG 1

1부산대학교

Accredited

ABSTRACT

In this paper, we propose an efficient on-line handwritten digit recognition base on Convex-Concave curves feature which is extracted by a chain code sequence using Smith-Waterman alignment algorithm. The time sequential signal from mouse movement on the writing pad is described as a sequence of consecutive points on the x-y plane. So, we can create data-set which are successive and time-sequential pixel position data by preprocessing. Data preprocessed is used for Convex-Concave curves feature extraction. This feature is scale-, translation-, and rotation-invariant. The extracted specific feature is fed to a Smith-Waterman alignment algorithm, which in turn classifies it as one of the nine digits. In comparison with backpropagation neural network, Smith-Waterman alignment has the more outstanding performance.

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