This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04)
Global Shape Normalization for Handwritten Chinese Character Recognition: A New Method
Kokubunji, Tokyo, Japan
October 26-October 29
ISBN: 0-7695-2187-8
Cheng-Lin Liu, Hitachi, Ltd.
Katsumi Marukawa, Hitachi, Ltd.
Nonlinear normalization (NLN) based on line density equalization has been widely used in handwritten Chinese character recognition (HCCR). Our previous results showed that global transformation methods, including moment normalization and a newly proposed bi-moment method, generate smooth normalized shapes at lower computation effort while yielding comparable recognition accuracies. This paper proposes a new global transformation method, named modified centroid-boundary alignment (MCBA) method, for HCCR. The previous CBA method can efficiently correct the skewness of centroid by quadratic curve fitting but fails to adjust the inner density. The MCBA method adds a simple trigonometric (sine) function onto quadratic function to adjust the inner density. The amplitude of the sine wave is estimated from the centroids of half images. Experiments on the ETL9B and JEITA-HP databases show that the MCBA method yields comparably high accuracies to the NLN and bi-moment methods and shows complementariness.
Citation:
Cheng-Lin Liu, Katsumi Marukawa, "Global Shape Normalization for Handwritten Chinese Character Recognition: A New Method," iwfhr, pp.300-305, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), 2004
Usage of this product signifies your acceptance of the Terms of Use.