Efficient Shape Retrieval Under Partial Matching

Indexing into large database systems is essential for a number of applications. This paper presents a new indexing structure, which overcomes an important restriction of a previous indexing technique using a recently developed theorem from the domain of matrix analysis. Specifically, given a set of distance values computed by distance function, which do not necessarily satisfy the triangle inequality, this paper shows that computing its nearest distance values that obey the properties of a metric enables us to overcome the limitations of the previous indexing algorithm. We demonstrate the proposed framework in the context of a recognition task.