Corner detection and classification of simple objects in low-depth resolution range images

Abstract

This paper deals with corner detection of simple geometric objects in quantized range images. Low depth resolution and noise introduce challenges in edge and corner detection. Corner detection and classification is based on layer by layer depth data extraction and morphologic operations. Appearance based heuristics are applied to identify different corner types defined in this paper. Both computer generated and captured range images are dealt with. Synthetic range images have arbitrary range resolution while captured images are based on the sensor used. Real world data is collected using a structured light based sensor to provide dense range map.