Detection of incomplete enclosures of rectangular shape in remotely sensed images

An Application of Artificial Intelligence to Support the Discovering of Roman Centuriation Remains

“…While no incontrovertible evidence of centuriation was located, satellite data proved to be of use in surveying medium-scale rural patterns. In [6] authors developed an approach for detection of ruins of livestock enclosures in alpine areas captured by high-resolution remotely sensed images. These are structures usually of approximately rectangular shape and appear in images as faint fragmented contours in complex background.…”

“…In Figure 1 it is shown how main streets and pathways of the Italian city of Marcianise, in province of Caserta, match the same organization of Roman Centuriation. The automatic recognition of these remains is a relevant and challenging activity in the field of smart archaeology [6]. In fact, nowadays the study of such archaeological remains is still made manually and it is not trivial because original division are partially lost.…”

Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images

“…This paper follows our work presented in [24]. Here, we give a more detailed description of the methods, design a more efficient detector of initial candidate locations (Section II), report on the results of application of our approach to a large region in the Silvretta Alps (Section V), and extend our experimental part (Section VI) by comparing the discrimination ability of the introduced and alternative features for our task.…”

“…The normalization constant was set such that λ(θ) is a unit vector, which gave us better results than for the normalization constant equal to the sum of the weights used in [10]. More implementation details can be found in [24]. Note that we did not compare the rectangularity feature with the whole approach developed in [10] because it is based on additional features not appropriate in the case of enclosures.…”