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Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. Our solution approximates the boundary of the sensor network by determining the inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.