(untitled) (diségno, 2024)
Between 1304 and 1309, Pietro de’Crescenzi drew up the Opus ruralium commodorum, perhaps the first agronomic treatise of the medieval period, in which it is possible to find a first taxonomic classification of gardens according to the social importance of their owner. The formal rules of the Italian garden remained unchanged until the 18th century, but unfortunately, little ‘original’ evidence of these jewels remains, because they were destroyed, abandoned or modified over the centuries; very often the proof of their existence can be found in artistic representations or in the treatises of the time. In this research, the landscape features of the Italian garden are investigated, and some automated Machine Learning algorithms are experimented to find symmetries between the plant and decorative elements that characterise it. Although automated symmetry detection has already demonstrated applicability in several disciplines, it is recently showing a new and not yet fully explored potential in art through the development of computer vision; however, some procedural and algorithmic aspects present numerous challenges and problems. For this reason, starting from an examination of the state of the art of current Imaging Detection solutions, we evaluate their applicability in the search for symmetries within artistic representations of Italian gardens.