%0 Journal Article
	%A Tossaporn Kachanubal and  Somkait Udomhunsakul
	%D 2008
	%J International Journal of Geotechnical and Geological Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 15, 2008
	%T Rock Textures Classification Based on Textural and Spectral Features
	%U https://publications.waset.org/pdf/8816
	%V 15
	%X In this paper, we proposed a method to classify each
type of natural rock texture. Our goal is to classify 26 classes of rock
textures. First, we extract five features of each class by using
principle component analysis combining with the use of applied
spatial frequency measurement. Next, the effective node number of
neural network was tested. We used the most effective neural
network in classification process. The results from this system yield
quite high in recognition rate. It is shown that high recognition rate
can be achieved in separation of 26 stone classes.
	%P 658 - 664