In this paper, we present a new fully-automated approach. to analyze the geometry of homogeneous leaves from numerical images produced by a desktop scanner. Our method is focused on two particular aspects: data coupling, specifically weights and areas matching, and numerical deletion of petioles,. both in a. large-scale analysis context. The process limits user interaction, the leaves segmentation is self conditioned and realized by a k-means classification giving the threshold value (or each image. The results are arranged according to the leaves disposition on the scanner pane: the leaves labels are defined by recognitions of rows, obtained by c1ustering. The result layout cases the data coupling, i.e. the matching of individual leaves measures produced· by different devices. We do also propose a new automated petiole removal procedure. The deletion method, applied to each single leaf, uses à morphological analysis from the leaf medial line. The process is adaptive, without expert calibration. The method is implemented in a ready to use application. Tests hold on several data sets show satisfactory results on a wide range of leaf shapes.