Community Research and Development Information Service - CORDIS

Performance evaluation of tree object matching

In this report, we present and evaluate an algorithm that exploits the Multi-Scale Singularity Trees (MSSTs) for image matching. Two versions of the algorithm is presented: an exact and an approximation. Several experiments are conducted to empirically evaluate the MSST matching algorithm under image distortions. Further, the performance of the MSST matching algorithm is measured on three databases: the ORL face database, magazine covers, and the COIL database. Finally, the performance is compared with algorithms based on the Scale Invariant Feature Transform (SIFT) and the Position of Catastrophes (CAT).

The intended application is image matching and this highlights the strengths and weaknesses of the three methods MSST, the SIFT, or the CAT. The potential end-user application is image databases, which are found as medical X-ray images, newspaper archives, and private digital image archives.

Our work has focused on the MSST structure and algorithms for matching these. Our results do not compare with the state-of-the-art of the SIFT algorithm, since we are limited algorithmically to handle only a few number of catastrophes, and thus can only obtain state-of-the-art results for blurry images. However, for these few number of parameters, our matching results are better than the SIFT algorithms, which indicate that the tree structure is closer linked to the important image information than the SIFT features. Thus, it is our opinion that the MSSTs and the matching algorithm presented in this report deserve further attention.

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