An efficient electronic archiving approach for office automation
Hazem Mokhtar El-Bakry, Nikos E. Mastorakis · 2009
Recentlly, electronic archives are becoming very important for office automation. Minimizing the size of the stored data in electronic archive is a main issue to reduce the phyzical storage area. In this paper, the effect of different types of Arabic fonts on electronic archives size is discussed. Simunation results show that PDF is the best file format for storage of the Arabic documents in electronic archive. Furthermore, an approach for fast word detection is in PDF file is presented. Such aprroch uses fast neural networks (FNNs) implemented in the frequency domain. The operation of these networks relies on performing cross correlation in the frequency domain rather than spatial one. It is proved mathematically and practically that the number of computation steps required for the presented FNNs is less than that needed by conventional neural networks (CNNs). Simulation results using MATLAB confirm the theoretical computations.