Document Type

Report

Date

2-4-2011

Embargo Period

3-30-2011

Keywords

Image segmentation, Cramér–Rao bound, Affine bias mode

Language

English

Disciplines

Electrical and Computer Engineering

Description/Abstract

Image segmentation is a very important step in image analysis, and performance evaluation of segmentation algorithms plays a key role both in developing efficient algorithms and in selecting suitable methods for the given tasks. Although a number of publications have appeared on segmentation methodology and segmentation performance evaluation, little attention has been given to statistically bounding the performance of image segmentation algorithms. In this paper, a modified Cramér–Rao bound combined with the Affine bias model is employed to determine the performance limit of image segmentation algorithms. A fuzzy segmentation formulation is considered, of which hard segmentation is a special case. Experimental results are obtained where we compare the performance of several representative image segmentation algorithms with the derived bound on both synthetic and real-world image data.

Source

local input

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