Techniques to identify printed and handwritten text in scanned documents di®er signi¯cantly. In this paper, we address the question of how to discriminate between each type of writing on registration forms. Registration-form documents consist of various type zones, such as printed text, handwriting, table, image, noise, etc., so segmenting the various zones is a challenge. We adopt herein an approach called \ multiscale-region projection" to identify printed text and handwriting. An important aspect of our approach is the use of multiscale techniques to segment document images. A new set of projection features extracted from each zone is also proposed. The classi¯cation rules are mining and are used to discern printed text and table lines from handwritten text. The proposed system was tested on 11 118 samples in two registrationform-image databases. Some possible measures of e±ciency are computed, and in each case the proposed approach performs better than traditional methods.