This paper presents Cantag, an open source software toolkit for building Marker-based Vision (MBV) systems that can identify and accurately locate printed markers in three dimensions. The extensibility of the system makes it ideal for dynamic location and pose determination in pervasive computing systems. Unlike prior MBV systems, Cantag supports multiple fiducial shapes, payload types, data sizes and image processing algorithms in one framework. It allows the application writer to generate a custom tag design and associated optimised executable for any given application. The system includes a test harness which can be used to quantify, compare and contrast the performance of different designs. This paper explores the design space of tags within the Cantag system, and describes the design parameters and performance characteristics which an application writer can use to select the best tag system for any given scenario. It presents quantitative analysis of different markers and processing algorithms, which are compared fairly for the first time.