Using local features for efficient layout analysis of ancient manuscripts

A binarization-free layout analysis method for ancient manuscripts is proposed, which identifies and localizes layout entities exploiting their structural similarities on the local level. Hence, the textual entities are disassembled into segments, and a part-based detection is done which employs local gradient features known from the field of object recognition, the Scale Invariant Feature Transform (SIFT), to describe these structures. Layout analysis is the first step in the process of document understanding; it identifies regions of interest and, hence, serves as input for other algorithms such as Optical Character Recognition (OCR). Moreover, the document layout allows scholars to establish the spatio-temporal origin, authenticate, or index a document. The layout entities considered in this approach include the body text, embellished initials, plain initials and headings.