Similarity Measure for Image Retrieval Based on Hausdorff Distance

Abstract

In general, it is difficult to segment accurately image regions or boundary contours and represent them by feature vectors for shape-based image query. Therefore, the object similarity is often computed by their boundaries. Hausdorff distance is nonlinear for computing distance, it can be used to measure the similarity between two patterns of points of edge images. Classical Hausdorff measure need to express image as a feature matrix firstly, then calculate feature values or feature vectors, so it is time-consuming. Otherwise, it is difficult for part pattern matching when shadow and noise existed. In this paper, an algorithm that use Hausdorff distance on the image boundaries to measure similarity is proposed. Experimental result has showed that the proposed algorithm is robust.

An Improved Automatic Algorithm for Global Eddy Tracking Using Satellite Altimeter Data

“…The HD has been widely used in image matching and shape comparison tasks and can be applied to measure the similarity between two patterns of points in images denoting edges [38][39][40]. Given two finite point sets = {a1, a2, a3... am} and = {b1, b2, b3... bn}, the HD is defined as follows: …”