Detecting and Locating Partly Occluded Planar Parts by Clustering

In this paper I address the problem of recognizing and locating partly occluded industrial parts in two-dimensional space. The shapes of parts under study consist of linear and circular segments. Most man-made objects have such geometric primitives. Many industrial parts such as stamped parts and flat foundry castings can be considered planar because of their small thickness. Therefore the restrictions on the recognized parts are widely applicable to the industrial environment.A model-based object recognition method is introduced where the linear and circular segments are used as feature primitives to construct an attributed relational graph. Each node in the graph represents a primitive, and is described by the primitive’s geometric properties. The arc between any two nodes represents the geometric relation (distance, angle, etc.) between two primitives. In the feature extraction phase, the low-level primitives are extracted by dominant point detection, least-squares fitting and segment splitting-and-mer...