Report on assessment of MSSTs for 3 D Mathing Application

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We consider images as manifolds embedded in a hybrid high dimensional space of coordinates and features. Images are partitioned into segments based on the energy functional and mathemat- ical landmarks. The nesting of image segments in scale-space is used to construct image hierar- chies called Multi-Scale Singularity Trees (MSSTs). Two kinds of mathematical landmarks are proposed namely extremal points and saddle points.
We study the stability of the Extrema-Based MSSTs extracted from a series of smoothly changed generated images. The observed MSST transitions can be categorized into three cat- egories: changes of positions, changes of relations, and changes of connections. The stability comparison between Extrema-Based MSSTs and Saddle-Based MSSTs is also briefly presented.
We point out the equivalence between MSSTs and Multi-Scale Singularity Strings (MSSSs) and propose two sets of edit operations on MSSSs, one for Extrema-Based MSSSs and one for Saddle-Based MSSSs. Simple examples of editing MSSSs are also presented.
We describe a medical image database of volumetric CT scans of the craniofacial area and manually segmented teeth. The database is aimed at evaluating the image matching algorithm based on MSSTs.
Original languageEnglish
Number of pages34
Publication statusPublished - 2004

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