Content Based Image Retrieval Using Multiscale Top Points

A feasibility study for a new method for content based image retrieval is presented. First, an image representation using multiscale top points is introduced. This representation is validated using a minimal variance reconstruction algorithm. The image retrieval problem can now be translated into comparing distances between point sets. For this purpose the proportional transportation distance (PTD) is used. A method is proposed using multiscale top points and their reconstruction coefficients in the PTD to define these distances between images. We present some experiments with promising results on a database with face images.