Title :
Texture classification using statistical geometrical features
Author :
Chen, Yan ; Nixon, Mark S. ; Thomas, David W.
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Abstract :
This paper presents a new texture feature set based on the statistics of geometrical attributes of connected regions in a stack of binary images obtained from a texture image. Systematic evaluation using all the Brodatz textures shows that the new set outperforms the well-known statistical gray level dependence matrix, the recently proposed statistical feature matrix, and Liu´s features
Keywords :
feature extraction; geometry; image classification; image texture; statistics; Brodatz textures; binary images; connected regions; geometrical attributes; statistical geometrical features; texture classification; texture image; Computer science; Formal languages; Fourier transforms; Image texture analysis; Medical diagnosis; Pixel; Quality control; Remote sensing; Statistics; Stochastic processes;
Conference_Titel :
Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference
Conference_Location :
Austin, TX
Print_ISBN :
0-8186-6952-7
DOI :
10.1109/ICIP.1994.413767