Bottom-up document segmentation method based on textural features
A. M. Vil’kin, Ilia V. Safonov, M. A. Egorova · Pattern Recognition and Image Analysis · 2011
A bottom-up approach to segmentation of a scanned document into background, text, and image regions is considered. The image is partitioned into blocks at the first step. A series of texture features is computed for each block. The block type is determined on the basis of these features. Different variants of block arrangement and size, 26 texture variables, and four block type classification algorithms have been considered. The block type is corrected on the basis of adjacent region analysis at the second step. The error matrix and ICDAR 2007 criterion are used for result estimation.