Mendeley
TY  _  JOUR
ID  -  1394090814852637
TI  -  Persian Handwritten Word Recognition by Log-Polar Transform and Hidden Markov Model
JO  -  Nashriyyah -i Muhandisi -i Barq va Muhandisi -i Kampyutar -i Iran
JA  -  ES
LA  -  fa
SN  -  16823745
AU  -  Nadalinia Charei Q.
AU  -  Yaghmaie K.
AU  -  Fazlollahi Aghamalek H.
AU  -  Razavi S. M.
AD  -  دانشگاه سمنان
AD  -  دانشگاه سمنان
AD  -  دانشگاه بیرجند
AD  -  دانشگاه بیرجند
Y1  -  2014
PY  -  2014
VL  -  4
IS  -  
SP  -  103
EP  -  110
KW  -  Log-polar transform
hidden Markov model (HMM)
Persian handwritten word recognition
DO  -  
N2  -  In this paper a recognition system for Persian words is introduced which utilizes the local higher order of the log-polar image autocorrelation for feature extraction of Persian sub-words. This feature extraction technique brings up leads to a system robustness in cases of writing variations alteration like scaled or rotated handwritings. Also using the log-polar transform, the sub-word image sampling will be performed so that most of acquired samples will be centered in a certain area. The proposed method uses the discrete Hidden Markov’s Model (HMM) as a classifier. Furthermore a net of dictionaries were employed to increase the reliability and precision of the system output. Finally, the Iran-Shahr database is utilized to evaluate the system performance. Comparing the results of the proposed method and other previous methods, proves that a less sensitivity has been achieved by the proposed method about handwriting variations.
UR  - rimag.ir/en/Article/28070
L1  - rimag.ir/en/Article/Download/28070
ER  -  
