A non-supervised approach using Gabor filters for vine-plot detection in aerial images

Abstract

Vine-plot mapping and monitoring are crucial issues in land management, particularly for areas where vineyards are dominant, like in some French regions. In this context, the availability of an automatic tool for vineyard detection and characterization would be very useful. Due to the periodic patterns induced by this culture, frequency analysis appears to be a very suited tool for vineyard detection in aerial images. A recursive process using Fast Fourier Transform algorithm was developed to meet this need. This results in vine-plot segmentation, with boundaries in polygonal form and characterization with accurate estimation of interrow width and row orientation. To foster large-scale applications, tests and validation have been carried out on standard very high spatial resolution remote-sensing data. About 80% of vine plots have been well or under-segmented and 11.4% not detected at all. More than 84% of vineyard surface have been detected.