Towards Applying the OPRA Theory to Shape Similarity

TL;DR

This paper explores applying the OPRA theory to develop a human-like, qualitative shape similarity measure using simple predicates, aiming for cognitive plausibility in pattern recognition.

Contribution

It introduces a novel approach to shape similarity based on OPRA theory, emphasizing simple, human-applicable predicates for qualitative shape descriptions.

Findings

Proposes a shape similarity measure aligned with human cognition

Uses simple predicates for qualitative shape descriptions

Potential for improved pattern recognition applications

Abstract

The motivation for using qualitative shape descriptions is as follows: qualitative shape descriptions can implicitly act as a schema for measuring the similarity of shapes, which has the potential to be cognitively adequate. Then, shapes which are similar to each other would also be similar for a pattern recognition algorithm. There is substantial work in pattern recognition and computer vision dealing with shape similarity. Here with our approach to qualitative shape descriptions and shape similarity, the focus is on achieving a representation using only simple predicates that a human could even apply without computer support.