Shape Matching Using Point Context and Contour Segments

This paper proposes a novel method to generate robust contour partition points and applies them to produce point context and contour segment features for shape matching. The main idea is to match object shapes by matching contour partition points and contour segments. In contrast to typical shape context method, we do not consider the topological graph structure since our approach is only considering a small number of partition points rather than full contour points. The experimental results demonstrate that our method is able to produce correct results in the presence of articulations, stretching, and contour deformations. The most significant scientific contributions of this paper include (i) the introduction of a novel partition point extraction technique for point context and contour segments as well as (ii) a new fused similarity measure for object matching and recognition, and (iii) the impressive robustness of the method in an object retrieval scenario as well as in a real application for environmental microorganism recognition.