Gaussian localized active contours for multitemporal analysis of urban tree crowns

Abstract

This paper introduces geometric active contours and level-set evolution for the semi-automatic monitoring of urban trees in a sequence of very high resolution images. In our implementation active contours locally identify tree crown image regions using a localized data energy term and competition of energy forces between adjacent contours. In a first step, a surface fitting operation generates a set of ellipses which are used as the initial state of contour optimization. Contours evolve simultaneously using a Gaussian localized energy term which considers the energy of the evolving contour and its neighboring contours. We incorporate prior information into the multitemporal analysis, as contours are propagated and optimized through the sequence of images. We report the implementation and obtained results using a set of two and four aerial images of a residential area in New York, USA and Enschede, The Netherlands, respectively.