Classification of binary textures using the 1-D Boolean model

Author

Garcia-Sevilla, Pedro ; Petrou, Maria

Author_Institution

Dept. of Comput. Sci., Univ. Jaume I, Castellon, Spain

Volume

8

Issue

10

fYear

1999

fDate

10/1/1999 12:00:00 AM

Firstpage

1457

Lastpage

1462

Abstract

The one-dimensional (1-D) Boolean model is used to calculate features for the description of binary textures. Each two-dimensional (2-D) texture is converted into several 1-D strings by scanning it according to raster vertical, horizontal or Hilbert sequences. Several different probability distributions for the segment lengths created this way are used to model their distribution. Therefore, each texture is described by a set of Boolean models. Classification is performed by calculating the overlapping probability between corresponding models. The method is evaluated with the help of 32 different binary textures, and the pros and cons of the approach are discussed

Keywords

Boolean algebra; image classification; image sequences; image texture; statistical analysis; 1D Boolean model; 1D strings; Hilbert sequence; binary texture classification; feature extraction; horizontal sequence; image scanning; overlapping probability; parameter estimation; probability distributions; raster; segment lengths; vertical sequence; Computer science; Councils; Distributed computing; Distribution functions; Feature extraction; Image texture analysis; Parameter estimation; Probability distribution; Shape; Two dimensional displays;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.791973

Filename

791973