  In This paper we presented new approach for cursive Arabic text recognition
system. The objective is to propose methodology analytical offline recognition
of handwritten Arabic for rapid implementation. The first part in the writing
recognition system is the preprocessing phase is the preprocessing phase to
prepare the data was introduces and extracts a set of simple statistical
features by two methods : from a window which is sliding long that text line
the right to left and the approach VH2D (consists in projecting every character
on the abscissa, on the ordinate and the diagonals 45{\deg} and 135{\deg}) . It
then injects the resulting feature vectors to Hidden Markov Model (HMM) and
combined the two HMM by multi-stream approach.
