Abstract
In these last years, many works have been published in the video indexing and retrieval field. However, few are the methods that have been designed to Arabic video. This paper's aim is to achieve a new approach for Arabic news video indexing based on embedded text as the information source and Knowledge extraction techniques to provide a conceptual description of video content. Firstly, we applied a low level processing in order to detect and recognize the video texts. Then, we extract the conceptual information including name of person, Organization and location using local grammars that have been implemented with the linguistic platform NooJ. Our proposed approach was tested on a large collection of Arabic TV news and experimental results were satisfactory.