الفهرس 
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Abstract
Current research suggests building a system based on the digital image processing and implement the image retrieval techniques and face recognition techniques for determine the student identity in distance examination system using both faceprint and handprint, this research presented a proposed system used to provide a solution to the problem existing deficiencies in the distance examination especially face print and hand print seen as biological prints, which can never be falsified and where God gives us these biological properties which different between all people even twins. Current research studying a number of artificial intelligence techniques used in digital image processing and extracted image features. The proposed system works as follows: Firstly; this before the Distance Examinations, in this stage database1 which use in matching process are created. In it the faces images are saved. To getting the face image the system deal with four types of images Single student image, Students among group image, Vail image and hand image. In the first three types the image’s face detected and cutted then saved in the main database. Then used the feature extracted method for getting the face’s features, the feature extraction techniques used in this system are Gray level co-occurrence matrix (GLCM), Color moments (CM) and Color coherence vector (CCV). The face image, face features and student name are saved in database1. Secondly; this done during the exam. It aims to getting the decision is this the student or no by using query image. To determine the student the query image feature will be extracted by using feature extracted methods then matching with the images features in database1. The percentage of similarity calculated by using Weighted Euclidean Distance then this percentage sorted in descending order to the nearest 15 image. The student has been identified depending on the most percentage of similarity. The proposed system has been created effectively and successful to meet the goals required of it. The proposed system was developed in order to increase the efficiency and effectiveness. This done in 2 phases: Phase 1: in it number of face images in the database has been increased by dealing with the images of the students in groups. Depending of this the number of images has been increased for each student from 5 images to 10 images. This has helped for increase the performance. The second phase, for increase the efficiency of the system hand image had been added and used as handprint. Hands images acquired by using digital camera every person in sample has four images for his hands two for left hand one for inside and another for outside, also for right hand, so that 60 hand images had been acquired. Then we extracted the features of hand images. The fusion between face print and palm print to make a decision, in order to the decision become more performance and effectiveness.