Title :
Selection of color texture features from Reduced Size Chromatic Co-occurrence Matrices
Author :
Porebski, Alice ; Vandenbroucke, Nicolas ; Macaire, Ludovic
Author_Institution :
Ecole d´´Ing. du Pas-de-Calais (EIPC), Longuenesse, France
Abstract :
In this paper, we present a feature selection scheme which builds a low-dimensional feature space for texture classification. These features are extracted from texture descriptors called Reduced-Size Chromatic Co-occurrence Matrices (RSCCMs) which result from color quantization. Thanks to experimental results achieved with VisTex and OuTex databases, we show that the analysis of Haralick features extracted from these RSCCMs, themselves computed from color images coded in 28 different color spaces, provides satisfying classification results while significantly reducing the processing time.
Keywords :
data compression; feature extraction; image classification; image coding; image colour analysis; image texture; color image coding; color quantization; color texture feature selection; feature extraction; reduced-size chromatic cooccurrence matrices; texture classification; texture descriptors; Feature extraction; Image analysis; Image color analysis; Image databases; Image processing; Image texture analysis; Quantization; Signal processing; Spatial databases; Supervised learning;
Conference_Titel :
Signal and Image Processing Applications (ICSIPA), 2009 IEEE International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-5560-7
DOI :
10.1109/ICSIPA.2009.5478602