In this paper a document analysis tool for historical manuscripts is proposed. The goal is to automatically segment layout components of the page, that is text, pictures and decorations. We specifically focused on the pictures, proposing a set of visual features able to identify significant pictures and separating them from all the floral and abstract decorations. The analysis is performed by blocks using a limited set of color and texture features, including a new texture descriptor particularly effective for this task, namely Gradient Spatial Dependency Matrix. The feature vectors are processed by an embedding procedure which allows increased performance in later SVM classification.