In this paper, we present a novel computational framework for assisting and assessing memorization tasks. Such a framework can be used in any cases where certain level of memorization is needed, like in memorizing words/sentences, learning (programming) language structures, etc. We aim to identify the common memorization steps followed in various disciplines and then automate some of these steps to enhance memorization process. Particularly, we focus on annotation of texts (used for memorization) based on state of the art image processing techniques. Once texts are annotated and optionally commented, personalized tests can be automatically generated, focusing on the weakness of a particular student. These tests can further enhance the memorization process. As a case study, we have implemented the framework for a classical example of memorization: memorizing the Qur’an, the sacred book in Islam. Qur’an memorization is a well-known process since the early days of Islam and represents an ideal case for implementing the proposed framework.