An Improved ANOVA Algorithm for Crop Mark Extraction from Large Aerial Images Using Semantics

In this paper, an approach based on the analysis of variance (ANOVA) for the extraction of crop marks from aerial images is improved by means of preliminary analyses and semantic processing of the extracted objects. The paper falls in the field of digitalization of images for archaeology, assisting expert users in the detection of un-excavated sites. The methodology is improved by a preliminary analysis of local curvatures, able to determine the most suitable direction for the ANOVA formulation. Then, a semantic processing, based on the knowledge of the shape of the target wide line, is performed to delete false positive detections. Sample analyses are always performed on actual images and prove the capability of the method to discriminate the most significant marks, aiding archaeologists in the analysis of huge amount of data.