Region-Based Hierarchical Image Matching
Sinisa Todorovic and Narendra Ahuja
Computer Vision and Robotics Laboratory
Beckman Institute for Advanced Science and Technology
University of Illinois at Urbana-Champaign,
405 N. Mathews Ave., Urbana, IL 61801, U.S.A.
Tel. +1-217-333-1837 or +1-217-265-9443, Fax: +1-217-244-8371
July 17, 2007 DRAFT
This paper presents an approach to region-based hierarchical image matching, where, given two
images, the goal is to identify the largest part in image 1 and its match in image 2 having the
maximum similarity measure defined in terms of geometric and photometric properties of regions (e.g.,
area, boundary shape, and color), as well as region topology (e.g., recursive embedding of regions).
To this end, each image is represented by a tree of recursively embedded regions, obtained by a
multiscale segmentation algorithm. This allows us to pose image matching as the tree matching problem.
To overcome imaging noise, one-to-one, many-to-one, and many-to-many node correspondences are
allowed. The trees are first augmented with new nodes generated by merging adjacent sibling nodes,