Evaluating a similarity between volume data using critical point graphs and contour trees.

Nowadays, a huge volume datasets has been generated from numerical simulations and measurement equipments. However the classification and reference has been usually performed manually, such as vision or experience of a measurement engineer . There still has not been revealed efficient techniques for searching similarity between volumetric datasets. On the other hand, some techniques for expressing the structure of the volume data in a simple figure are proposed. In this report, Critical Point Graphs and Contour Trees are used as a key to the similar level judgment from among those techniques . A similar level is judged to some data, and the merit and the weak point of each technique are clarified .