## Location

University of Utah

## Start Date

6-12-1996 2:00 PM

## Description

This is the second paper in a series of papers (1],(2] that represent continuing work on analyzing visual signatures of ground vehicles using fractal analysis techniques. In this paper, two new dimension estimate solutions based on sub-optimal covers are introduced. These dimension estimate problems and their solutions are akin to the box dimension definition, which is the standard estimate for fractal dimension. However, they represent a dual solution problem to the standard box counting algorithm for estimating the box dimension and thus fractal dimension. These methods are discussed and compared with the standard box counting algorithm using a set of standard brownian random images.

Sub-Optimal Covers for Measuring Dractal Dimension

University of Utah

This is the second paper in a series of papers (1],(2] that represent continuing work on analyzing visual signatures of ground vehicles using fractal analysis techniques. In this paper, two new dimension estimate solutions based on sub-optimal covers are introduced. These dimension estimate problems and their solutions are akin to the box dimension definition, which is the standard estimate for fractal dimension. However, they represent a dual solution problem to the standard box counting algorithm for estimating the box dimension and thus fractal dimension. These methods are discussed and compared with the standard box counting algorithm using a set of standard brownian random images.