In this paper, we present a general guideline to establish the relation between a distribution
model and its corresponding similarity estimation. A rich set of distance metrics, such as …

Assessing similarity between features is a key step in object recognition and scene
categorization tasks. We argue that knowledge on the distribution of distances generated by …

We propose a new distance measure, called Complement weighted sum of minimal
distances, between finite sets in\mathbb Z^ n and evaluate its usefulness for shape …

This paper is a response to the similarity measure and pattern recognition problem of
Mitchell that was published in Pattern Recognition Letters, 2003. The purpose of this paper …

This article presents a signal matching algorithm that can select an appropriate window size
adaptively so as to obtain both precise and stable estimation of correspondences. Matching …

This paper investigates general properties of distance functions defined over digitized
space. We assume that a distance between two points is defined as the length of a shortest …

In many computer vision algorithms, a metric or similarity measure is used to determine the
distance between two features. The Euclidean or SSD (sum of the squared differences) …

Computing object distance using image processing is an important research area in the field
of computer vision and robot navigation applications. In this paper we have proposed a new …

The notion of similarity is a fundamental concept in different scientific fields. Similarity
measures aim at quantifying the extent to which objects resemble each other. This paper is …