Creator:
Contributor:
Korbicz, Józef - red. ; Uciński, Dariusz - red.
Title:
Surrogate data: a novel approach to object detection
Group publication title:
Subject and Keywords:
surrogate data ; optimal paths ; fuzzy connectedness
Abstract:
In the present study a novel method is introduced to detect meaningful regions of a gray-level noisy images of binary structures. The method consists in generating surrogate data for an analyzed image. A surrogate image has the same (or almost the same) power spectrum and histogram of gray-level values as the original one but is random otherwise. ; Then minmax paths are generated in the original image, each characterized by its length, minmax intensity and the intensity of the starting point. If the probability of the existence of a path with the same characteristics but within surrogate images is lower than some user-specified threshold, it is concluded that the path in the original image passes through a meaningful object. The performance of the method is tested on images corrupted by noise with varying intensity.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Date:
Resource Type:
DOI:
Pages:
Source:
AMCS, Volume 20, Number 3 (2010) ; click here to follow the link