Target Detection Algorithm Based on Fractal Features of Variance

Author

Dong Wen-ming ; Wu Le-hua ; Jiang De-lei ; Han Chao

Author_Institution

Chongqing Commun. Inst., Chongqing

fYear

2009

fDate

23-24 May 2009

Firstpage

1

Lastpage

4

Abstract

Fractal dimension has been widly used for man-made targets detection because it can reflects an image´s roughness. However, it always performs not very well because the other feature- intercept which reflects the the speed of surface change is neglected. Aimed to this problem, an improved algorithm about how to calculate the fractal dimension based on variance property of fractional brownian motion is presented and utilized with intercept feature together. And then,a detection algorithm is proposed. Experiments show that the method has good adaptability and improved the efficiency, whether the background or the objects has changed or not.

Keywords

Brownian motion; feature extraction; fractals; object detection; fractal variance feature detection; fractional Brownian motion; target detection algorithm; Brownian motion; Change detection algorithms; Chaotic communication; Detection algorithms; Fractals; Geometry; Object detection; Rough surfaces; Surface fitting; Surface roughness;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-3893-8

Electronic_ISBN

978-1-4244-3894-5

Type

conf

DOI

10.1109/IWISA.2009.5073157

Filename

5073157