Classification of binary textures using the 1-D Boolean model
The one-dimensional (1-D) Boolean model is used to calculate features for the description of binary textures. Each two-dimensional (2D) 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.
feature extraction statistical models texture analysis