This research present's a new approach for Arabic Text-dependent Writer Identification. It dependent on feature based classification approach using the Discrete Contourlet transform. The coefficient of CT is used as a feature vector. This feature vector is used to extract the Eigen value and Eigen vector using PCA method. The PCA (Principal Component Analysis) is used to reduce the dimensionality of the feature vector .Which is used as an input to Multi_layer perceptron (MLP) neural network to match with testing feature vector. Experimental tests have been carried out on a set of samples of Arabic handwriting words corresponding to 50 writers. Some promising experimental results are reported.

Locating files in an exact time is considered one of the greatest problems and the tedious process in universities nowadays. This problem becomes greater when the university has a large number of departments and transactions, as well as the documents are moving from one department to another. Especially, developing countries that have many problems and unstable environment and that may lead to lost or damage the important documents that influence on the decision making. Furthermore, the traditional manner not only wasted the time and energy, but also the paper cost for printing copies of required file. And with the advancement of technology and the increase of Internet users, documents are still being sent in Iraqi universities manually between departments. Although the higher education and scientific research ministry was recommended the public universities for using modern technologies during the daily transactions between the departments or amongst the units. Therefore, this study sought to design and evaluate the prototype system which tracks movements of the documents from one department to another as well as check the completion rate for each department. For providing opportunities to assess how well the use of e-file tracking system meets the needs of management units in universities. The systems implementation research notes the need to fit between tasks, technologies and users. Thus, this empirical study utilized the task technology fit model for this purpose. The results from selected participants indicated that all the factors significant effect on the employee’s performance in E-file Tracking System, excepted, task characteristics. This study will be contributed to reduce the corruption and enhance the transparency and help the decision-makers make the right decision at the right time.