Interest Operators in Close-range Object Reconstruction

This paper investigates the use of interest operators for feature detection and the generation of high-accuracy object measurement, modelling, texturing and visualization. Interest operators are required as a preliminary step in the surface measurement process, to find features points for matching across multiple images. Three interest operators, namely the Förstner, SUSAN and FAST algorithms are assessed based on speed, feature detection rate and localization. The FAST operator is found to be the optimal interest operator for close-range object reconstruction. An image pre-processing algorithm, namely the Wallis filter, is also investigated and results indicate that it greatly enhances interest operator performance.