A Data Structure for the 3D Hough Transform for Plane Detection

The Hough Transform is a well-known method for detecting parametrized objects. It is the de facto standard for the detection of lines and circles in 2-dimensional data sets. For 3D it has attained little attention so far. Apart from computational costs, the main problem is the representation of the accumulator: Usual implementations favor geometrical objects with certain parameters due to uneven sampling of the parameter space. In this paper we present a novel approach to design the accumulator focusing on achieving the same size for each cell. The proposed accumulator is compared to previously known designs.