Shape feature abstraction in knowledge-based analysis of manufactured products

The authors focus on shape feature recognition based on the differential depth perception filter, which reduces the number of topological entities. By defining features in terms of loops, as opposed to defining them in terms of low level topological entities, substantial geometric as well as topological variation among features is captured. The space of entities in which the search for features is finally performed is loops. The reduction of this search space is first performed by the filter, and then by creating the loops from edges, both of which are significant. This assists in the reduction of combinatorial explosion. Considerable success in feature recognition has been achieved for parts with varying topology and geometry and for parts with a relatively large number of topological entities