In this paper, we describe how meta-data of indexation can be extracted from historical document images using an interactive process with a software called AGORA. The algorithms involved in AGORA use two maps to segment noisy images: a shape map that focuses on connected components and a background map that provides information on white areas corresponding to block separations in the page. Using a first segmentation result obtained by using these two maps, meta-data can be extracted according to scenarios produced by the users. These scenarios are defined very simply during an interactive stage. The user is able to make processing sequences adapted to the different kinds of images he is likely to meet and according to the desired meta-data. Finally, we describe different experimentations that have been done during the BVH project to test the usability and the performances of AGORA software.