  Historical newspapers are a source of research for the human and social
sciences. However, these image collections are difficult to read by machine due
to the low quality of the print, the lack of standardization of the pages in
addition to the low quality photograph of some files. This paper presents the
processing model of a topic navigation system in historical newspaper page
images. The general procedure consists of four modules which are: segmentation
of text sub-images and text extraction, preprocessing and representation,
induced topic extraction and representation, and document viewing and retrieval
interface. The algorithmic and technological approaches of each module are
described and the initial test results about a collection covering a range of
28 years are presented.
