@article{(Open Science Index):https://publications.waset.org/pdf/11092,
	  title     = {Texture Feature Extraction using Slant-Hadamard Transform},
	  author    = {M. J. Nassiri and  A. Vafaei and  A. Monadjemi},
	  country	= {},
	  institution	= {},
	  abstract     = {Random and natural textures classification is still
one of the biggest challenges in the field of image processing and
pattern recognition. In this paper, texture feature extraction using
Slant Hadamard Transform was studied and compared to other
signal processing-based texture classification schemes. A
parametric SHT was also introduced and employed for natural
textures feature extraction. We showed that a subtly modified
parametric SHT can outperform ordinary Walsh-Hadamard
transform and discrete cosine transform. Experiments were carried
out on a subset of Vistex random natural texture images using a
kNN classifier.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {5},
	  year      = {2008},
	  pages     = {1561 - 1565},
	  ee        = {https://publications.waset.org/pdf/11092},
	  url   	= {https://publications.waset.org/vol/17},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 17, 2008},